add speed parameter

cpp/README.md

@@ -4,6 +4,8 @@ High-performance text-to-speech inference using ONNX Runtime.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Requirements

cpp/example_onnx.cpp

@@ -10,6 +10,7 @@ namespace fs = std::filesystem;
 struct Args {
     std::string onnx_dir = "../assets/onnx";
     int total_step = 5;
+    float speed = 1.05f;
     int n_test = 4;
     std::vector<std::string> voice_style = {"../assets/voice_styles/M1.json"};
     std::vector<std::string> text = {
@@ -36,6 +37,7 @@ Args parseArgs(int argc, char* argv[]) {
         std::string arg = argv[i];
         if (arg == "--onnx-dir" && i + 1 < argc) args.onnx_dir = argv[++i];
         else if (arg == "--total-step" && i + 1 < argc) args.total_step = std::stoi(argv[++i]);
+        else if (arg == "--speed" && i + 1 < argc) args.speed = std::stof(argv[++i]);
         else if (arg == "--n-test" && i + 1 < argc) args.n_test = std::stoi(argv[++i]);
         else if (arg == "--voice-style" && i + 1 < argc) args.voice_style = splitString(argv[++i], ',');
         else if (arg == "--text" && i + 1 < argc) args.text = splitString(argv[++i], '|');
@@ -51,6 +53,7 @@ int main(int argc, char* argv[]) {
     // --- 1. Parse arguments --- //
     Args args = parseArgs(argc, argv);
     int total_step = args.total_step;
+    float speed = args.speed;
     int n_test = args.n_test;
     std::string save_dir = args.save_dir;
     std::vector<std::string> voice_style_paths = args.voice_style;
@@ -84,9 +87,9 @@ int main(int argc, char* argv[]) {
         
         auto result = timer("Generating speech from text", [&]() {
             if (batch) {
-                return text_to_speech->batch(memory_info, text_list, style, total_step);
+                return text_to_speech->batch(memory_info, text_list, style, total_step, speed);
             } else {
-                return text_to_speech->call(memory_info, text_list[0], style, total_step);
+                return text_to_speech->call(memory_info, text_list[0], style, total_step, speed);
             }
         });
         

cpp/helper.cpp

@@ -160,7 +160,8 @@ TextToSpeech::SynthesisResult TextToSpeech::_infer(
     Ort::MemoryInfo& memory_info,
     const std::vector<std::string>& text_list,
     const Style& style,
-    int total_step
+    int total_step,
+    float speed
 ) {
     int bsz = text_list.size();
     
@@ -213,6 +214,11 @@ TextToSpeech::SynthesisResult TextToSpeech::_infer(
     auto* dur_data = dp_outputs[0].GetTensorMutableData<float>();
     std::vector<float> duration(dur_data, dur_data + bsz);
     
+    // Apply speed factor to duration
+    for (auto& dur : duration) {
+        dur /= speed;
+    }
+    
     // Create new tensors for text encoder (previous ones were moved)
     text_ids_tensor = intArrayToTensor(memory_info, text_ids, text_ids_shape);
     text_mask_tensor = arrayToTensor(memory_info, text_mask, text_mask_shape);
@@ -370,6 +376,7 @@ TextToSpeech::SynthesisResult TextToSpeech::call(
     const std::string& text,
     const Style& style,
     int total_step,
+    float speed,
     float silence_duration
 ) {
     if (style.getTtlShape()[0] != 1) {
@@ -381,7 +388,7 @@ TextToSpeech::SynthesisResult TextToSpeech::call(
     float dur_cat = 0.0f;
     
     for (const auto& chunk : text_list) {
-        auto result = _infer(memory_info, {chunk}, style, total_step);
+        auto result = _infer(memory_info, {chunk}, style, total_step, speed);
         
         if (wav_cat.empty()) {
             wav_cat = result.wav;
@@ -406,9 +413,10 @@ TextToSpeech::SynthesisResult TextToSpeech::batch(
     Ort::MemoryInfo& memory_info,
     const std::vector<std::string>& text_list,
     const Style& style,
-    int total_step
+    int total_step,
+    float speed
 ) {
-    return _infer(memory_info, text_list, style, total_step);
+    return _infer(memory_info, text_list, style, total_step, speed);
 }
 
 // ============================================================================

cpp/helper.h

@@ -91,6 +91,7 @@ public:
         const std::string& text,
         const Style& style,
         int total_step,
+        float speed = 1.05f,
         float silence_duration = 0.3f
     );
     
@@ -98,7 +99,8 @@ public:
         Ort::MemoryInfo& memory_info,
         const std::vector<std::string>& text_list,
         const Style& style,
-        int total_step
+        int total_step,
+        float speed = 1.05f
     );
     
     int getSampleRate() const { return sample_rate_; }
@@ -108,7 +110,8 @@ private:
         Ort::MemoryInfo& memory_info,
         const std::vector<std::string>& text_list,
         const Style& style,
-        int total_step
+        int total_step,
+        float speed = 1.05f
     );
     Config cfgs_;
     UnicodeProcessor* text_processor_;

csharp/ExampleONNX.cs

@@ -12,6 +12,7 @@ namespace Supertonic
             public bool UseGpu { get; set; } = false;
             public string OnnxDir { get; set; } = "assets/onnx";
             public int TotalStep { get; set; } = 5;
+            public float Speed { get; set; } = 1.05f;
             public int NTest { get; set; } = 4;
             public List<string> VoiceStyle { get; set; } = new List<string> { "assets/voice_styles/M1.json" };
             public List<string> Text { get; set; } = new List<string> 
@@ -42,6 +43,9 @@ namespace Supertonic
                     case "--total-step" when i + 1 < args.Length:
                         result.TotalStep = int.Parse(args[++i]);
                         break;
+                    case "--speed" when i + 1 < args.Length:
+                        result.Speed = float.Parse(args[++i]);
+                        break;
                     case "--n-test" when i + 1 < args.Length:
                         result.NTest = int.Parse(args[++i]);
                         break;
@@ -67,6 +71,7 @@ namespace Supertonic
             // --- 1. Parse arguments --- //
             var parsedArgs = ParseArgs(args);
             int totalStep = parsedArgs.TotalStep;
+            float speed = parsedArgs.Speed;
             int nTest = parsedArgs.NTest;
             string saveDir = parsedArgs.SaveDir;
             var voiceStylePaths = parsedArgs.VoiceStyle;
@@ -96,11 +101,11 @@ namespace Supertonic
                 {
                     if (batch)
                     {
-                        return textToSpeech.Batch(textList, style, totalStep);
+                        return textToSpeech.Batch(textList, style, totalStep, speed);
                     }
                     else
                     {
-                        return textToSpeech.Call(textList[0], style, totalStep);
+                        return textToSpeech.Call(textList[0], style, totalStep, speed);
                     }
                 });
 

csharp/Helper.cs

@@ -194,7 +194,7 @@ namespace Supertonic
             return (noisyLatent, latentMask);
         }
 
-        private (float[] wav, float[] duration) _Infer(List<string> textList, Style style, int totalStep)
+        private (float[] wav, float[] duration) _Infer(List<string> textList, Style style, int totalStep, float speed = 1.05f)
         {
             int bsz = textList.Count;
             if (bsz != style.TtlShape[0])
@@ -222,6 +222,12 @@ namespace Supertonic
             };
             using var dpOutputs = _dpOrt.Run(dpInputs);
             var durOnnx = dpOutputs.First(o => o.Name == "duration").AsTensor<float>().ToArray();
+            
+            // Apply speed factor to duration
+            for (int i = 0; i < durOnnx.Length; i++)
+            {
+                durOnnx[i] /= speed;
+            }
 
             // Run text encoder
             var textEncInputs = new List<NamedOnnxValue>
@@ -284,7 +290,7 @@ namespace Supertonic
             return (wavTensor.ToArray(), durOnnx);
         }
 
-        public (float[] wav, float[] duration) Call(string text, Style style, int totalStep, float silenceDuration = 0.3f)
+        public (float[] wav, float[] duration) Call(string text, Style style, int totalStep, float speed = 1.05f, float silenceDuration = 0.3f)
         {
             if (style.TtlShape[0] != 1)
             {
@@ -297,7 +303,7 @@ namespace Supertonic
 
             foreach (var chunk in textList)
             {
-                var (wav, duration) = _Infer(new List<string> { chunk }, style, totalStep);
+                var (wav, duration) = _Infer(new List<string> { chunk }, style, totalStep, speed);
 
                 if (wavCat.Count == 0)
                 {
@@ -317,9 +323,9 @@ namespace Supertonic
             return (wavCat.ToArray(), new float[] { durCat });
         }
 
-        public (float[] wav, float[] duration) Batch(List<string> textList, Style style, int totalStep)
+        public (float[] wav, float[] duration) Batch(List<string> textList, Style style, int totalStep, float speed = 1.05f)
         {
-            return _Infer(textList, style, totalStep);
+            return _Infer(textList, style, totalStep, speed);
         }
     }
 

csharp/README.md

@@ -4,6 +4,8 @@ This guide provides examples for running TTS inference using `ExampleONNX.cs`.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Installation

go/README.md

@@ -4,6 +4,8 @@ This guide provides examples for running TTS inference using `example_onnx.go`.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Installation

go/example_onnx.go

@@ -15,6 +15,7 @@ type Args struct {
 	useGPU      bool
 	onnxDir     string
 	totalStep   int
+	speed       float64
 	nTest       int
 	voiceStyle  []string
 	text        []string
@@ -28,6 +29,7 @@ func parseArgs() *Args {
 	flag.BoolVar(&args.useGPU, "use-gpu", false, "Use GPU for inference (default: CPU)")
 	flag.StringVar(&args.onnxDir, "onnx-dir", "assets/onnx", "Path to ONNX model directory")
 	flag.IntVar(&args.totalStep, "total-step", 5, "Number of denoising steps")
+	flag.Float64Var(&args.speed, "speed", 1.05, "Speech speed factor (higher = faster)")
 	flag.IntVar(&args.nTest, "n-test", 4, "Number of times to generate")
 	flag.StringVar(&args.saveDir, "save-dir", "results", "Output directory")
 	flag.BoolVar(&args.batch, "batch", false, "Enable batch mode (multiple text-style pairs)")
@@ -63,6 +65,7 @@ func main() {
 	// --- 1. Parse arguments --- //
 	args := parseArgs()
 	totalStep := args.totalStep
+	speed := float32(args.speed)
 	nTest := args.nTest
 	saveDir := args.saveDir
 	voiceStylePaths := args.voiceStyle
@@ -123,7 +126,7 @@ func main() {
 
 		if batch {
 			Timer("Generating speech from text", func() interface{} {
-				w, d, err := textToSpeech.Batch(textList, style, totalStep)
+				w, d, err := textToSpeech.Batch(textList, style, totalStep, speed)
 				if err != nil {
 					fmt.Printf("Error generating speech: %v\n", err)
 					os.Exit(1)
@@ -134,7 +137,7 @@ func main() {
 			})
 		} else {
 			Timer("Generating speech from text", func() interface{} {
-				w, d, err := textToSpeech.Call(textList[0], style, totalStep, 0.3)
+				w, d, err := textToSpeech.Call(textList[0], style, totalStep, speed, 0.3)
 				if err != nil {
 					fmt.Printf("Error generating speech: %v\n", err)
 					os.Exit(1)

go/helper.go

@@ -572,7 +572,7 @@ func (tts *TextToSpeech) sampleNoisyLatent(durOnnx []float32) ([][][]float64, []
 	return noisyLatent, latentMask
 }
 
-func (tts *TextToSpeech) _infer(textList []string, style *Style, totalStep int) ([]float32, []float32, error) {
+func (tts *TextToSpeech) _infer(textList []string, style *Style, totalStep int, speed float32) ([]float32, []float32, error) {
 	bsz := len(textList)
 
 	// Process text
@@ -597,6 +597,11 @@ func (tts *TextToSpeech) _infer(textList []string, style *Style, totalStep int)
 	durTensor := dpOutputs[0].(*ort.Tensor[float32])
 	defer durTensor.Destroy()
 	durOnnx := durTensor.GetData()
+	
+	// Apply speed factor to duration
+	for i := range durOnnx {
+		durOnnx[i] /= speed
+	}
 
 	// Encode text
 	textIDsTensor2 := IntArrayToTensor(textIDs, textIDsShape)
@@ -691,14 +696,14 @@ func (tts *TextToSpeech) _infer(textList []string, style *Style, totalStep int)
 }
 
 // Call synthesizes speech from a single text with automatic chunking
-func (tts *TextToSpeech) Call(text string, style *Style, totalStep int, silenceDuration float32) ([]float32, float32, error) {
+func (tts *TextToSpeech) Call(text string, style *Style, totalStep int, speed float32, silenceDuration float32) ([]float32, float32, error) {
 	chunks := chunkText(text, 0)
 	
 	var wavCat []float32
 	var durCat float32
 
 	for i, chunk := range chunks {
-		wav, duration, err := tts._infer([]string{chunk}, style, totalStep)
+		wav, duration, err := tts._infer([]string{chunk}, style, totalStep, speed)
 		if err != nil {
 			return nil, 0, err
 		}
@@ -724,8 +729,8 @@ func (tts *TextToSpeech) Call(text string, style *Style, totalStep int, silenceD
 }
 
 // Batch synthesizes speech from multiple texts
-func (tts *TextToSpeech) Batch(textList []string, style *Style, totalStep int) ([]float32, []float32, error) {
+func (tts *TextToSpeech) Batch(textList []string, style *Style, totalStep int, speed float32) ([]float32, []float32, error) {
-	return tts._infer(textList, style, totalStep)
+	return tts._infer(textList, style, totalStep, speed)
 }
 
 func (tts *TextToSpeech) Destroy() {

java/ExampleONNX.java

@@ -15,6 +15,7 @@ public class ExampleONNX {
         boolean useGpu = false;
         String onnxDir = "assets/onnx";
         int totalStep = 5;
+        float speed = 1.05f;
         int nTest = 4;
         List<String> voiceStyle = Arrays.asList("assets/voice_styles/M1.json");
         List<String> text = Arrays.asList(
@@ -41,6 +42,9 @@ public class ExampleONNX {
                 case "--total-step":
                     if (i + 1 < args.length) result.totalStep = Integer.parseInt(args[++i]);
                     break;
+                case "--speed":
+                    if (i + 1 < args.length) result.speed = Float.parseFloat(args[++i]);
+                    break;
                 case "--n-test":
                     if (i + 1 < args.length) result.nTest = Integer.parseInt(args[++i]);
                     break;
@@ -76,6 +80,7 @@ public class ExampleONNX {
             // --- 1. Parse arguments --- //
             Args parsedArgs = parseArgs(args);
             int totalStep = parsedArgs.totalStep;
+            float speed = parsedArgs.speed;
             int nTest = parsedArgs.nTest;
             String saveDir = parsedArgs.saveDir;
             List<String> voiceStylePaths = parsedArgs.voiceStyle;
@@ -111,7 +116,7 @@ public class ExampleONNX {
                 if (batch) {
                     ttsResult = Helper.timer("Generating speech from text", () -> {
                         try {
-                            return textToSpeech.batch(textList, style, totalStep, env);
+                            return textToSpeech.batch(textList, style, totalStep, speed, env);
                         } catch (Exception e) {
                             throw new RuntimeException(e);
                         }
@@ -119,7 +124,7 @@ public class ExampleONNX {
                 } else {
                     ttsResult = Helper.timer("Generating speech from text", () -> {
                         try {
-                            return textToSpeech.call(textList.get(0), style, totalStep, 0.3f, env);
+                            return textToSpeech.call(textList.get(0), style, totalStep, speed, 0.3f, env);
                         } catch (Exception e) {
                             throw new RuntimeException(e);
                         }

java/Helper.java

@@ -154,7 +154,7 @@ class TextToSpeech {
         this.ldim = config.ttl.latentDim;
     }
     
-    private TTSResult _infer(List<String> textList, Style style, int totalStep, OrtEnvironment env) 
+    private TTSResult _infer(List<String> textList, Style style, int totalStep, float speed, OrtEnvironment env) 
             throws OrtException {
         int bsz = textList.size();
         
@@ -182,6 +182,11 @@ class TextToSpeech {
             duration = (float[]) dpValue;
         }
         
+        // Apply speed factor to duration
+        for (int i = 0; i < duration.length; i++) {
+            duration[i] /= speed;
+        }
+        
         // Encode text
         Map<String, OnnxTensor> textEncInputs = new HashMap<>();
         textEncInputs.put("text_ids", textIdsTensor);
@@ -301,7 +306,7 @@ class TextToSpeech {
     /**
      * Synthesize speech from a single text with automatic chunking
      */
-    public TTSResult call(String text, Style style, int totalStep, float silenceDuration, OrtEnvironment env) 
+    public TTSResult call(String text, Style style, int totalStep, float speed, float silenceDuration, OrtEnvironment env) 
             throws OrtException {
         List<String> chunks = Helper.chunkText(text, 0);
         
@@ -309,7 +314,7 @@ class TextToSpeech {
         float durCat = 0.0f;
         
         for (int i = 0; i < chunks.size(); i++) {
-            TTSResult result = _infer(Arrays.asList(chunks.get(i)), style, totalStep, env);
+            TTSResult result = _infer(Arrays.asList(chunks.get(i)), style, totalStep, speed, env);
             
             float dur = result.duration[0];
             int wavLen = (int) (sampleRate * dur);
@@ -344,9 +349,9 @@ class TextToSpeech {
     /**
      * Batch synthesize speech from multiple texts
      */
-    public TTSResult batch(List<String> textList, Style style, int totalStep, OrtEnvironment env) 
+    public TTSResult batch(List<String> textList, Style style, int totalStep, float speed, OrtEnvironment env) 
             throws OrtException {
-        return _infer(textList, style, totalStep, env);
+        return _infer(textList, style, totalStep, speed, env);
     }
     
     public void close() throws OrtException {

java/README.md

@@ -4,6 +4,8 @@ This guide provides examples for running TTS inference using `ExampleONNX.java`.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Installation

nodejs/README.md

@@ -4,6 +4,8 @@ Node.js implementation for TTS inference. Uses ONNX Runtime to generate speech f
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Requirements

nodejs/example_onnx.js

@@ -15,6 +15,7 @@ function parseArgs() {
         useGpu: false,
         onnxDir: 'assets/onnx',
         totalStep: 5,
+        speed: 1.05,
         nTest: 4,
         voiceStyle: ['assets/voice_styles/M1.json'],
         text: ['This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen.'],
@@ -32,6 +33,8 @@ function parseArgs() {
             args.onnxDir = process.argv[++i];
         } else if (arg === '--total-step' && i + 1 < process.argv.length) {
             args.totalStep = parseInt(process.argv[++i]);
+        } else if (arg === '--speed' && i + 1 < process.argv.length) {
+            args.speed = parseFloat(process.argv[++i]);
         } else if (arg === '--n-test' && i + 1 < process.argv.length) {
             args.nTest = parseInt(process.argv[++i]);
         } else if (arg === '--voice-style' && i + 1 < process.argv.length) {
@@ -55,6 +58,7 @@ async function main() {
     // --- 1. Parse arguments --- //
     const args = parseArgs();
     const totalStep = args.totalStep;
+    const speed = args.speed;
     const nTest = args.nTest;
     const saveDir = args.saveDir;
     const voiceStylePaths = args.voiceStyle.map(p => path.resolve(__dirname, p));
@@ -79,9 +83,9 @@ async function main() {
         
         const { wav, duration } = await timer('Generating speech from text', async () => {
             if (batch) {
-                return await textToSpeech.batch(textList, style, totalStep);
+                return await textToSpeech.batch(textList, style, totalStep, speed);
             } else {
-                return await textToSpeech.call(textList[0], style, totalStep);
+                return await textToSpeech.call(textList[0], style, totalStep, speed);
             }
         });
         

nodejs/helper.js

@@ -114,7 +114,7 @@ class TextToSpeech {
         return { noisyLatent, latentMask };
     }
 
-    async _infer(textList, style, totalStep) {
+    async _infer(textList, style, totalStep, speed = 1.05) {
         if (textList.length !== style.ttl.dims[0]) {
             throw new Error('Number of texts must match number of style vectors');
         }
@@ -133,6 +133,11 @@ class TextToSpeech {
         
         const durOnnx = Array.from(dpResult.duration.data);
         
+        // Apply speed factor to duration
+        for (let i = 0; i < durOnnx.length; i++) {
+            durOnnx[i] /= speed;
+        }
+        
         const textEncResult = await this.textEncOrt.run({
             text_ids: intArrayToTensor(textIds, textIdsShape),
             style_ttl: style.ttl,
@@ -185,7 +190,7 @@ class TextToSpeech {
         return { wav, duration: durOnnx };
     }
 
-    async call(text, style, totalStep, silenceDuration = 0.3) {
+    async call(text, style, totalStep, speed = 1.05, silenceDuration = 0.3) {
         if (style.ttl.dims[0] !== 1) {
             throw new Error('Single speaker text to speech only supports single style');
         }
@@ -194,7 +199,7 @@ class TextToSpeech {
         let durCat = 0;
         
         for (const chunk of textList) {
-            const { wav, duration } = await this._infer([chunk], style, totalStep);
+            const { wav, duration } = await this._infer([chunk], style, totalStep, speed);
             
             if (wavCat === null) {
                 wavCat = wav;
@@ -210,8 +215,8 @@ class TextToSpeech {
         return { wav: wavCat, duration: [durCat] };
     }
 
-    async batch(textList, style, totalStep) {
+    async batch(textList, style, totalStep, speed = 1.05) {
-        return await this._infer(textList, style, totalStep);
+        return await this._infer(textList, style, totalStep, speed);
     }
 }
 

py/README.md

@@ -4,6 +4,8 @@ This guide provides examples for running TTS inference using `example_onnx.py`.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed. Adjust the speed factor to make speech faster or slower while maintaining natural quality.
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Installation
@@ -85,6 +87,28 @@ This will:
 
 **Note**: When using batch mode (`--batch`), automatic text chunking is disabled. Use non-batch mode for long-form text synthesis.
 
+### Example 5: Adjusting Speech Speed
+Control the speed of speech synthesis:
+```bash
+# Faster speech (speed > 1.0)
+uv run example_onnx.py \
+  --voice-style assets/voice_styles/F2.json \
+  --text "This text will be synthesized at a faster pace." \
+  --speed 1.2
+
+# Slower speech (speed < 1.0)
+uv run example_onnx.py \
+  --voice-style assets/voice_styles/M2.json \
+  --text "This text will be synthesized at a slower, more deliberate pace." \
+  --speed 0.9
+```
+
+This will:
+- Use `--speed 1.2` to generate faster speech
+- Use `--speed 0.9` to generate slower speech
+- Default speed is 1.05 if not specified
+- Recommended speed range is between 0.9 and 1.5 for natural-sounding results
+
 ## Available Arguments
 
 | Argument | Type | Default | Description |
@@ -92,6 +116,7 @@ This will:
 | `--use-gpu` | flag | False | Use GPU for inference (with CPU fallback) |
 | `--onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
 | `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
+| `--speed` | float | 1.05 | Speech speed factor (higher = faster, lower = slower) |
 | `--n-test` | int | 4 | Number of times to generate each sample |
 | `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) |
 | `--text` | str+ | (long default text) | Text(s) to synthesize |

py/example_onnx.py

@@ -26,6 +26,12 @@ def parse_args():
     parser.add_argument(
         "--total-step", type=int, default=5, help="Number of denoising steps"
     )
+    parser.add_argument(
+        "--speed",
+        type=float,
+        default=1.05,
+        help="Speech speed (default: 1.05, higher = faster)",
+    )
     parser.add_argument(
         "--n-test", type=int, default=4, help="Number of times to generate"
     )
@@ -62,6 +68,7 @@ print("=== TTS Inference with ONNX Runtime (Python) ===\n")
 # --- 1. Parse arguments --- #
 args = parse_args()
 total_step = args.total_step
+speed = args.speed
 n_test = args.n_test
 save_dir = args.save_dir
 voice_style_paths = args.voice_style
@@ -84,9 +91,9 @@ for n in range(n_test):
     print(f"\n[{n+1}/{n_test}] Starting synthesis...")
     with timer("Generating speech from text"):
         if batch:
-            wav, duration = text_to_speech.batch(text_list, style, total_step)
+            wav, duration = text_to_speech.batch(text_list, style, total_step, speed)
         else:
-            wav, duration = text_to_speech(text_list[0], style, total_step)
+            wav, duration = text_to_speech(text_list[0], style, total_step, speed)
     if not os.path.exists(save_dir):
         os.makedirs(save_dir)
     for b in range(bsz):

py/helper.py

@@ -86,7 +86,7 @@ class TextToSpeech:
         return noisy_latent, latent_mask
 
     def _infer(
-        self, text_list: list[str], style: Style, total_step: int
+        self, text_list: list[str], style: Style, total_step: int, speed: float = 1.05
     ) -> tuple[np.ndarray, np.ndarray]:
         assert (
             len(text_list) == style.ttl.shape[0]
@@ -96,6 +96,7 @@ class TextToSpeech:
         dur_onnx, *_ = self.dp_ort.run(
             None, {"text_ids": text_ids, "style_dp": style.dp, "text_mask": text_mask}
         )
+        dur_onnx = dur_onnx / speed
         text_emb_onnx, *_ = self.text_enc_ort.run(
             None,
             {"text_ids": text_ids, "style_ttl": style.ttl, "text_mask": text_mask},
@@ -120,7 +121,12 @@ class TextToSpeech:
         return wav, dur_onnx
 
     def __call__(
-        self, text: str, style: Style, total_step: int, silence_duration: float = 0.3
+        self,
+        text: str,
+        style: Style,
+        total_step: int,
+        speed: float = 1.05,
+        silence_duration: float = 0.3,
     ) -> tuple[np.ndarray, np.ndarray]:
         assert (
             style.ttl.shape[0] == 1
@@ -129,7 +135,7 @@ class TextToSpeech:
         wav_cat = None
         dur_cat = None
         for text in text_list:
-            wav, dur_onnx = self._infer([text], style, total_step)
+            wav, dur_onnx = self._infer([text], style, total_step, speed)
             if wav_cat is None:
                 wav_cat = wav
                 dur_cat = dur_onnx
@@ -142,9 +148,9 @@ class TextToSpeech:
         return wav_cat, dur_cat
 
     def batch(
-        self, text_list: list[str], style: Style, total_step: int
+        self, text_list: list[str], style: Style, total_step: int, speed: float = 1.05
     ) -> tuple[np.ndarray, np.ndarray]:
-        return self._infer(text_list, style, total_step)
+        return self._infer(text_list, style, total_step, speed)
 
 
 def length_to_mask(lengths: np.ndarray, max_len: Optional[int] = None) -> np.ndarray:

rust/README.md

@@ -4,6 +4,8 @@ This guide provides examples for running TTS inference using Rust.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Installation

rust/src/example_onnx.rs

@@ -26,6 +26,10 @@ struct Args {
     #[arg(long, default_value = "5")]
     total_step: usize,
 
+    /// Speech speed factor (higher = faster)
+    #[arg(long, default_value = "1.05")]
+    speed: f32,
+
     /// Number of times to generate
     #[arg(long, default_value = "4")]
     n_test: usize,
@@ -53,6 +57,7 @@ fn main() -> Result<()> {
     // --- 1. Parse arguments --- //
     let args = Args::parse();
     let total_step = args.total_step;
+    let speed = args.speed;
     let n_test = args.n_test;
     let voice_style_paths = &args.voice_style;
     let text_list = &args.text;
@@ -85,11 +90,11 @@ fn main() -> Result<()> {
 
         let (wav, duration) = if batch {
             timer("Generating speech from text", || {
-                text_to_speech.batch(text_list, &style, total_step)
+                text_to_speech.batch(text_list, &style, total_step, speed)
             })?
         } else {
             let (w, d) = timer("Generating speech from text", || {
-                text_to_speech.call(&text_list[0], &style, total_step, 0.3)
+                text_to_speech.call(&text_list[0], &style, total_step, speed, 0.3)
             })?;
             (w, vec![d])
         };

rust/src/helper.rs

@@ -484,6 +484,7 @@ impl TextToSpeech {
         text_list: &[String],
         style: &Style,
         total_step: usize,
+        speed: f32,
     ) -> Result<(Vec<f32>, Vec<f32>)> {
         let bsz = text_list.len();
 
@@ -511,7 +512,12 @@ impl TextToSpeech {
         })?;
 
         let (_, duration_data) = dp_outputs["duration"].try_extract_tensor::<f32>()?;
-        let duration: Vec<f32> = duration_data.to_vec();
+        let mut duration: Vec<f32> = duration_data.to_vec();
+        
+        // Apply speed factor to duration
+        for dur in duration.iter_mut() {
+            *dur /= speed;
+        }
 
         // Encode text
         let style_ttl_value = Value::from_array(style.ttl.clone())?;
@@ -584,6 +590,7 @@ impl TextToSpeech {
         text: &str,
         style: &Style,
         total_step: usize,
+        speed: f32,
         silence_duration: f32,
     ) -> Result<(Vec<f32>, f32)> {
         let chunks = chunk_text(text, None);
@@ -592,7 +599,7 @@ impl TextToSpeech {
         let mut dur_cat: f32 = 0.0;
 
         for (i, chunk) in chunks.iter().enumerate() {
-            let (wav, duration) = self._infer(&[chunk.clone()], style, total_step)?;
+            let (wav, duration) = self._infer(&[chunk.clone()], style, total_step, speed)?;
             
             let dur = duration[0];
             let wav_len = (self.sample_rate as f32 * dur) as usize;
@@ -619,8 +626,9 @@ impl TextToSpeech {
         text_list: &[String],
         style: &Style,
         total_step: usize,
+        speed: f32,
     ) -> Result<(Vec<f32>, Vec<f32>)> {
-        self._infer(text_list, style, total_step)
+        self._infer(text_list, style, total_step, speed)
     }
 }
 

swift/README.md

@@ -4,6 +4,8 @@ This guide provides examples for running TTS inference using `example_onnx`.
 
 ## 📰 Update News
 
+**2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Installation

swift/Sources/ExampleONNX.swift

@@ -5,6 +5,7 @@ struct Args {
     var useGpu: Bool = false
     var onnxDir: String = "assets/onnx"
     var totalStep: Int = 5
+    var speed: Float = 1.05
     var nTest: Int = 4
     var voiceStyle: [String] = ["assets/voice_styles/M1.json"]
     var text: [String] = ["This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."]
@@ -33,6 +34,11 @@ func parseArgs() -> Args {
                 args.totalStep = Int(arguments[i + 1]) ?? 5
                 i += 1
             }
+        case "--speed":
+            if i + 1 < arguments.count {
+                args.speed = Float(arguments[i + 1]) ?? 1.05
+                i += 1
+            }
         case "--n-test":
             if i + 1 < arguments.count {
                 args.nTest = Int(arguments[i + 1]) ?? 4
@@ -102,13 +108,13 @@ struct ExampleONNX {
                 
                 if args.batch {
                     let result = try timer("Generating speech from text") {
-                        try textToSpeech.batch(args.text, style, args.totalStep)
+                        try textToSpeech.batch(args.text, style, args.totalStep, speed: args.speed)
                     }
                     wav = result.wav
                     duration = result.duration
                 } else {
                     let result = try timer("Generating speech from text") {
-                        try textToSpeech.call(args.text[0], style, args.totalStep, silenceDuration: 0.3)
+                        try textToSpeech.call(args.text[0], style, args.totalStep, speed: args.speed, silenceDuration: 0.3)
                     }
                     wav = result.wav
                     duration = [result.duration]

swift/Sources/Helper.swift

@@ -453,7 +453,7 @@ class TextToSpeech {
         self.sampleRate = cfgs.ae.sample_rate
     }
     
-    private func _infer(_ textList: [String], _ style: Style, _ totalStep: Int) throws -> (wav: [Float], duration: [Float]) {
+    private func _infer(_ textList: [String], _ style: Style, _ totalStep: Int, speed: Float = 1.05) throws -> (wav: [Float], duration: [Float]) {
         let bsz = textList.count
         
         // Process text
@@ -479,10 +479,15 @@ class TextToSpeech {
                                       runOptions: nil)
         
         let durationData = try dpOutputs["duration"]!.tensorData() as Data
-        let duration = durationData.withUnsafeBytes { ptr in
+        var duration = durationData.withUnsafeBytes { ptr in
             Array(ptr.bindMemory(to: Float.self))
         }
         
+        // Apply speed factor to duration
+        for i in 0..<duration.count {
+            duration[i] /= speed
+        }
+        
         // Encode text
         let textEncOutputs = try textEncOrt.run(withInputs: ["text_ids": textIdsValue, "style_ttl": style.ttl, "text_mask": textMaskValue],
                                                 outputNames: ["text_emb"],
@@ -576,14 +581,14 @@ class TextToSpeech {
         return (wav, duration)
     }
     
-    func call(_ text: String, _ style: Style, _ totalStep: Int, silenceDuration: Float) throws -> (wav: [Float], duration: Float) {
+    func call(_ text: String, _ style: Style, _ totalStep: Int, speed: Float = 1.05, silenceDuration: Float = 0.3) throws -> (wav: [Float], duration: Float) {
         let chunks = chunkText(text)
         
         var wavCat = [Float]()
         var durCat: Float = 0.0
         
         for (i, chunk) in chunks.enumerated() {
-            let result = try _infer([chunk], style, totalStep)
+            let result = try _infer([chunk], style, totalStep, speed: speed)
             
             let dur = result.duration[0]
             let wavLen = Int(Float(sampleRate) * dur)
@@ -605,8 +610,8 @@ class TextToSpeech {
         return (wavCat, durCat)
     }
     
-    func batch(_ textList: [String], _ style: Style, _ totalStep: Int) throws -> (wav: [Float], duration: [Float]) {
+    func batch(_ textList: [String], _ style: Style, _ totalStep: Int, speed: Float = 1.05) throws -> (wav: [Float], duration: [Float]) {
-        return try _infer(textList, style, totalStep)
+        return try _infer(textList, style, totalStep, speed: speed)
     }
 }
 

test_all.sh

@@ -108,6 +108,37 @@ NC='\033[0m' # No Color
 declare -a PASSED=()
 declare -a FAILED=()
 
+# Helper function to show statistics
+show_stats() {
+    local name=$1
+    local results_dir=$2
+    
+    if [ -d "$results_dir" ]; then
+        # Count .wav files
+        local file_count=$(find "$results_dir" -name "*.wav" -type f 2>/dev/null | wc -l | tr -d ' ')
+        
+        if [ "$file_count" -gt 0 ]; then
+            # Calculate total size
+            local total_size=0
+            while IFS= read -r file; do
+                if [ -f "$file" ]; then
+                    local size=$(stat -f%z "$file" 2>/dev/null || stat -c%s "$file" 2>/dev/null)
+                    total_size=$((total_size + size))
+                fi
+            done < <(find "$results_dir" -name "*.wav" -type f 2>/dev/null)
+            
+            # Calculate statistics
+            local total_size_mb=$(echo "scale=2; $total_size / 1024 / 1024" | bc)
+            local avg_size_kb=$(echo "scale=2; $total_size / $file_count / 1024" | bc)
+            
+            echo -e "${BLUE}[$name]${NC} 📊 Statistics:"
+            echo -e "${BLUE}[$name]${NC}   - Files generated: $file_count"
+            echo -e "${BLUE}[$name]${NC}   - Total size: ${total_size_mb} MB"
+            echo -e "${BLUE}[$name]${NC}   - Average file size: ${avg_size_kb} KB"
+        fi
+    fi
+}
+
 # Helper function to run tests
 run_test() {
     local name=$1
@@ -118,9 +149,19 @@ run_test() {
     echo -e "${BLUE}[$name]${NC} Running inference..."
     cd "$SCRIPT_DIR/$dir"
     
+    # Determine results directory based on the directory
+    local results_dir="$SCRIPT_DIR/$dir/results"
+    if [[ "$dir" == "cpp/build" ]]; then
+        results_dir="$SCRIPT_DIR/cpp/build/results"
+    fi
+    
     # Run command and prefix each output line with the language name
     if eval "$cmd" 2>&1 | sed "s/^/[$name] /"; then
         echo -e "${GREEN}[$name]${NC} ✓ Success"
+        
+        # Show statistics
+        show_stats "$name" "$results_dir"
+        
         PASSED+=("$name")
     else
         echo -e "${RED}[$name]${NC} ✗ Failed"

web/README.md

@@ -4,6 +4,8 @@ This example demonstrates how to use Supertonic in a web browser using ONNX Runt
 
 ## 📰 Update News
 
+**2025.11.19** - Added speed control slider to adjust speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
+
 **2025.11.19** - Added automatic text chunking for long-form inference. Long texts are split into chunks and synthesized with natural pauses.
 
 ## Features

web/helper.js

@@ -72,7 +72,7 @@ export class TextToSpeech {
         this.sampleRate = cfgs.ae.sample_rate;
     }
 
-    async _infer(textList, style, totalStep, progressCallback = null) {
+    async _infer(textList, style, totalStep, speed = 1.05, progressCallback = null) {
         const bsz = textList.length;
         
         // Process text
@@ -94,6 +94,11 @@ export class TextToSpeech {
         });
         const duration = Array.from(dpOutputs.duration.data);
         
+        // Apply speed factor to duration
+        for (let i = 0; i < duration.length; i++) {
+            duration[i] /= speed;
+        }
+        
         // Encode text
         const textEncOutputs = await this.textEncOrt.run({
             text_ids: textIdsTensor,
@@ -176,7 +181,7 @@ export class TextToSpeech {
         return { wav, duration };
     }
 
-    async call(text, style, totalStep, silenceDuration = 0.3, progressCallback = null) {
+    async call(text, style, totalStep, speed = 1.05, silenceDuration = 0.3, progressCallback = null) {
         if (style.ttl.dims[0] !== 1) {
             throw new Error('Single speaker text to speech only supports single style');
         }
@@ -185,7 +190,7 @@ export class TextToSpeech {
         let durCat = 0;
         
         for (const chunk of textList) {
-            const { wav, duration } = await this._infer([chunk], style, totalStep, progressCallback);
+            const { wav, duration } = await this._infer([chunk], style, totalStep, speed, progressCallback);
             
             if (wavCat.length === 0) {
                 wavCat = wav;
@@ -201,8 +206,8 @@ export class TextToSpeech {
         return { wav: wavCat, duration: [durCat] };
     }
 
-    async batch(textList, style, totalStep, progressCallback = null) {
+    async batch(textList, style, totalStep, speed = 1.05, progressCallback = null) {
-        return await this._infer(textList, style, totalStep, progressCallback);
+        return await this._infer(textList, style, totalStep, speed, progressCallback);
     }
 
     sampleNoisyLatent(duration, sampleRate, baseChunkSize, chunkCompress, latentDim) {

web/index.html

@@ -48,6 +48,12 @@
                             <input type="number" id="totalStep" value="5"
                                 min="1" max="50">
                         </div>
+                        
+                        <div class="section">
+                            <label for="speed">Speed (0.9-1.5 recommended):</label>
+                            <input type="number" id="speed" value="1.05"
+                                min="0.5" max="2.0" step="0.05">
+                        </div>
 
                     </div>
 

web/main.js

@@ -25,6 +25,7 @@ const textInput = document.getElementById('text');
 const voiceStyleSelect = document.getElementById('voiceStyleSelect');
 const voiceStyleInfo = document.getElementById('voiceStyleInfo');
 const totalStepInput = document.getElementById('totalStep');
+const speedInput = document.getElementById('speed');
 const generateBtn = document.getElementById('generateBtn');
 const statusBox = document.getElementById('statusBox');
 const statusText = document.getElementById('statusText');
@@ -186,6 +187,7 @@ async function generateSpeech() {
         `;
         
         const totalStep = parseInt(totalStepInput.value);
+        const speed = parseFloat(speedInput.value);
         
         showStatus('ℹ️ <strong>Generating speech from text...</strong>');
         const tic = Date.now();
@@ -194,6 +196,7 @@ async function generateSpeech() {
             text, 
             currentStyle, 
             totalStep,
+            speed,
             0.3,
             (step, total) => {
                 showStatus(`ℹ️ <strong>Denoising (${step}/${total})...</strong>`);