diff --git a/.gitignore b/.gitignore index ef0b1a55..eca783ac 100644 --- a/.gitignore +++ b/.gitignore @@ -70,3 +70,4 @@ xcuserdata/ # uv .build claude.md +logs/ diff --git a/MLX_AUDIO_GUIDE.md b/MLX_AUDIO_GUIDE.md new file mode 100644 index 00000000..b3a35fac --- /dev/null +++ b/MLX_AUDIO_GUIDE.md @@ -0,0 +1,126 @@ +# Chatterbox TTS Quick Reference + +Multilingual voice cloning TTS using mlx-audio on Apple Silicon. + +> **Note:** mlx-audio is already installed system-wide. Commands work from any folder. + + +--- + +## Web UI Usage + +The MLX Audio Studio provides a user-friendly interface for Text-to-Speech generation, including full support for Chatterbox voice cloning. + +### 1. Starting the Server + +Run the following command to start both the API server and the Web UI: + +```bash +python -m mlx_audio.server --start-ui +``` + +- **UI URL:** `http://localhost:3000` +- **API URL:** `http://localhost:8000` + +### 2. Using Chatterbox TTS + +1. **Select Model:** Choose `Chatterbox` from the **Model** dropdown menu. +2. **Reference Audio:** Click "Choose audio file..." to upload a 5-10 second clip of the voice you want to clone. + - *Note:* This is required for Chatterbox to work. +3. **Select Language:** Choose the target language from the **Language** dropdown (e.g., English, Chinese, Japanese). + - *Important:* Ensure this matches the text you are generating to avoid pronunciation issues. +4. **Adjust Settings:** + - **Emotion Exaggeration:** Controls expressiveness (0.0 - 1.0). Default is 0.5. Higher values make the voice more emotional but can be unstable. + - **Guidance Weight:** Controls how closely the model follows the text/audio conditioning. Default is 0.5. +5. **Generate:** Enter your text and click **Generate**. +6. **Download:** Click the download icon to save the generated audio as an MP3 file. + +### 3. Troubleshooting + +- **"Failed to fetch"**: If generation takes too long (Chatterbox is slow), the UI might timeout. We've increased the timeout to 5 minutes for Chatterbox. +- **Pronunciation issues**: If words sound wrong (e.g., "But I" -> "boot yi"), check that the **Language** dropdown is set correctly (e.g., to "English"). + +--- + +## CLI Usage + +### Basic Chinese TTS + +```bash +mlx_audio.tts.generate \ + --model mlx-community/chatterbox-fp16 \ + --text "你好，今天天气真不错！" \ + --lang_code zh \ + --ref_audio /path/to/reference_voice.mp3 \ + --file_prefix output +``` + +### All CLI Parameters + +| Parameter | Description | Default | +|-----------|-------------|---------| +| `--model` | Model path (use `mlx-community/chatterbox-fp16`) | Required | +| `--text` | Text to synthesize | Required | +| `--lang_code` | Language code (see below) | `en` | +| `--ref_audio` | Path to reference audio for voice cloning | Required | +| `--file_prefix` | Output filename prefix | `audio` | +| `--audio_format` | Output format: `wav`, `mp3`, `flac` | `wav` | +| `--exaggeration` | Emotion intensity (0.0-1.0) | `0.5` | +| `--cfg_scale` | Classifier-free guidance (lower = more stable) | `0.5` | +| `--temperature` | Sampling temperature | `0.8` | +| `--max_tokens` | Max tokens to generate (lower = faster) | `1000` | +| `--verbose` | Print detailed output | `false` | +| `--play` | Play audio after generation | `false` | + +--- + +## Python API + +```python +import mlx.core as mx +import soundfile as sf +import librosa +from mlx_audio.tts.utils import load_model + +# Load multilingual Chatterbox model +model = load_model('mlx-community/chatterbox-fp16') + +# Load reference audio (for voice cloning) +audio, sr = librosa.load('/path/to/reference.mp3', sr=24000, mono=True) +conds = model.prepare_conditionals(mx.array(audio), sr, exaggeration=0.5) + +# Generate Chinese speech +for result in model.generate( + text="你好，我是语音合成模型。", + conds=conds, + lang_code='zh', + max_new_tokens=300 +): + sf.write('output.wav', result.audio, result.sample_rate) +``` + +--- + +## Language Codes + +| Code | Language | Code | Language | +|------|----------|------|----------| +| `zh` | Chinese | `ja` | Japanese | +| `en` | English | `ko` | Korean | +| `es` | Spanish | `ar` | Arabic | +| `fr` | French | `hi` | Hindi | +| `de` | German | `ru` | Russian | +| `it` | Italian | `pt` | Portuguese | +| `nl` | Dutch | `pl` | Polish | +| `tr` | Turkish | `sv` | Swedish | + +Full list: `ar`, `da`, `de`, `el`, `en`, `es`, `fi`, `fr`, `he`, `hi`, `it`, `ja`, `ko`, `ms`, `nl`, `no`, `pl`, `pt`, `ru`, `sv`, `sw`, `tr`, `zh` + +--- + +## Tips + +1. **Reference audio**: Use 3-10 seconds of clean speech +2. **First run**: Downloads 2.6GB model (~5-10 min) +3. **Faster generation**: Use `--max_tokens 200` for short text +4. **exaggeration**: Higher = more emotional expression diff --git a/mlx_audio/server.py b/mlx_audio/server.py index fcdc47e3..1c506391 100644 --- a/mlx_audio/server.py +++ b/mlx_audio/server.py @@ -96,7 +96,6 @@ async def get_available_models(self): def int_or_float(value): - try: return int(value) except ValueError: @@ -164,6 +163,9 @@ class SpeechRequest(BaseModel): top_k: int | None = 40 repetition_penalty: float | None = 1.0 response_format: str | None = "mp3" + # Chatterbox-specific parameters + exaggeration: float | None = 0.5 + cfg_weight: float | None = 0.5 # Initialize the ModelProvider @@ -234,26 +236,69 @@ async def remove_model(model_name: str): async def generate_audio(model, payload: SpeechRequest, verbose: bool = False): - for result in model.generate( - payload.input, - voice=payload.voice, - speed=payload.speed, - gender=payload.gender, - pitch=payload.pitch, - lang_code=payload.lang_code, - ref_audio=payload.ref_audio, - ref_text=payload.ref_text, - temperature=payload.temperature, - top_p=payload.top_p, - top_k=payload.top_k, - repetition_penalty=payload.repetition_penalty, - ): - - sample_rate = result.sample_rate - buffer = io.BytesIO() - sf.write(buffer, result.audio, sample_rate, format=payload.response_format) - buffer.seek(0) - yield buffer.getvalue() + import base64 + import tempfile + + # Handle base64 ref_audio - decode to temp file + ref_audio = payload.ref_audio + temp_audio_path = None + + if ref_audio and ref_audio.startswith("data:"): + # Parse data URL: data:audio/wav;base64,XXXX... + try: + header, data = ref_audio.split(",", 1) + audio_bytes = base64.b64decode(data) + + # Determine file extension from MIME type + ext = ".wav" + if "audio/mp3" in header or "audio/mpeg" in header: + ext = ".mp3" + elif "audio/ogg" in header: + ext = ".ogg" + + # Save to temp file + with tempfile.NamedTemporaryFile(suffix=ext, delete=False) as f: + f.write(audio_bytes) + temp_audio_path = f.name + ref_audio = temp_audio_path + except Exception as e: + print(f"Error decoding base64 audio: {e}") + ref_audio = None + + # Debug logging + if ref_audio: + print( + f"[DEBUG] Using ref_audio: {ref_audio[:50] if isinstance(ref_audio, str) else 'array'}..." + ) + else: + print("[DEBUG] No ref_audio provided - will use default voice") + + try: + for result in model.generate( + payload.input, + voice=payload.voice, + speed=payload.speed, + gender=payload.gender, + pitch=payload.pitch, + lang_code=payload.lang_code, + ref_audio=ref_audio, + ref_text=payload.ref_text, + temperature=payload.temperature, + top_p=payload.top_p, + top_k=payload.top_k, + repetition_penalty=payload.repetition_penalty, + exaggeration=payload.exaggeration, + cfg_weight=payload.cfg_weight, + ): + sample_rate = result.sample_rate + buffer = io.BytesIO() + sf.write(buffer, result.audio, sample_rate, format=payload.response_format) + buffer.seek(0) + yield buffer.getvalue() + finally: + # Clean up temp file + if temp_audio_path and os.path.exists(temp_audio_path): + os.remove(temp_audio_path) @app.post("/v1/audio/speech") @@ -395,7 +440,7 @@ async def stt_realtime_transcriptions(websocket: WebSocket): if len(audio_buffer) % (sample_rate * 2) < len(audio_chunk_float): # Log every ~2 seconds of buffer print( - f"Speech detected ({speech_frames}/{num_frames} frames): buffer {len(audio_buffer)} samples ({len(audio_buffer)/sample_rate:.2f}s)" + f"Speech detected ({speech_frames}/{num_frames} frames): buffer {len(audio_buffer)} samples ({len(audio_buffer) / sample_rate:.2f}s)" ) else: silence_skip_count += 1 @@ -420,7 +465,7 @@ async def stt_realtime_transcriptions(websocket: WebSocket): ): should_process_initial = True print( - f"Processing initial chunk for real-time feedback: {initial_chunk_size/sample_rate:.2f}s, total buffer: {len(audio_buffer)/sample_rate:.2f}s" + f"Processing initial chunk for real-time feedback: {initial_chunk_size / sample_rate:.2f}s, total buffer: {len(audio_buffer) / sample_rate:.2f}s" ) # Process if we have enough silence after speech (end of utterance) elif ( @@ -429,13 +474,13 @@ async def stt_realtime_transcriptions(websocket: WebSocket): ): should_process_final = True print( - f"Processing due to silence gap: {time_since_last_speech:.2f}s silence, buffer: {len(audio_buffer)/sample_rate:.2f}s" + f"Processing due to silence gap: {time_since_last_speech:.2f}s silence, buffer: {len(audio_buffer) / sample_rate:.2f}s" ) # Or if buffer is getting too large (continuous speech) elif len(audio_buffer) >= max_chunk_size: should_process_final = True print( - f"Processing due to max buffer size: {len(audio_buffer)/sample_rate:.2f}s" + f"Processing due to max buffer size: {len(audio_buffer) / sample_rate:.2f}s" ) # Process initial chunk for real-time feedback @@ -542,7 +587,7 @@ async def stt_realtime_transcriptions(websocket: WebSocket): initial_chunk_processed = False last_process_time = current_time print( - f"Processed final chunk: {process_size} samples ({process_size/sample_rate:.2f}s), buffer cleared" + f"Processed final chunk: {process_size} samples ({process_size / sample_rate:.2f}s), buffer cleared" ) except Exception as e: diff --git a/mlx_audio/ui/app/text-to-speech/page.tsx b/mlx_audio/ui/app/text-to-speech/page.tsx index c9b503e4..fa907af1 100644 --- a/mlx_audio/ui/app/text-to-speech/page.tsx +++ b/mlx_audio/ui/app/text-to-speech/page.tsx @@ -64,13 +64,70 @@ export default function SpeechSynthesis() { const [liked, setLiked] = useState(null) const [selectedVoice, setSelectedVoice] = useState("conversational_a") + // Chatterbox-specific state + const [exaggeration, setExaggeration] = useState(0.5) + const [cfgWeight, setCfgWeight] = useState(0.5) + const [chatterboxLang, setChatterboxLang] = useState("en") + const [refAudioFile, setRefAudioFile] = useState(null) + const [refAudioBase64, setRefAudioBase64] = useState(null) + const [audioBlob, setAudioBlob] = useState(null) // Store blob for download + + // Chatterbox supported languages + const chatterboxLanguages = [ + { code: "en", name: "English" }, + { code: "ar", name: "Arabic" }, + { code: "da", name: "Danish" }, + { code: "de", name: "German" }, + { code: "el", name: "Greek" }, + { code: "es", name: "Spanish" }, + { code: "fi", name: "Finnish" }, + { code: "fr", name: "French" }, + { code: "he", name: "Hebrew" }, + { code: "hi", name: "Hindi" }, + { code: "it", name: "Italian" }, + { code: "ja", name: "Japanese" }, + { code: "ko", name: "Korean" }, + { code: "ms", name: "Malay" }, + { code: "nl", name: "Dutch" }, + { code: "no", name: "Norwegian" }, + { code: "pl", name: "Polish" }, + { code: "pt", name: "Portuguese" }, + { code: "ru", name: "Russian" }, + { code: "sv", name: "Swedish" }, + { code: "sw", name: "Swahili" }, + { code: "tr", name: "Turkish" }, + { code: "zh", name: "Chinese" }, + ] + const audioRef = useRef(null) + const fileInputRef = useRef(null) // Helper function to check if the model is a Marvis model const isMarvisModel = (modelName: string) => { return modelName.toLowerCase().includes("marvis") } + // Helper function to check if the model is a Chatterbox model + const isChatterboxModel = (modelName: string) => { + return modelName.toLowerCase().includes("chatterbox") + } + + // Handle reference audio file selection + const handleRefAudioChange = async (e: React.ChangeEvent) => { + const file = e.target.files?.[0] + if (file) { + setRefAudioFile(file) + // Convert to base64 for API + const reader = new FileReader() + reader.onload = () => { + const result = reader.result as string + // Remove data URL prefix to get just the base64 + setRefAudioBase64(result) + } + reader.readAsDataURL(file) + } + } + // Helper function to get available quantizations for a model const getAvailableQuantizations = (modelName: string) => { if (modelName === "Marvis-AI/marvis-tts-100m-v0.2") { @@ -134,28 +191,55 @@ export default function SpeechSynthesis() { const API_BASE_URL = process.env.NEXT_PUBLIC_API_BASE_URL || 'http://localhost'; const API_PORT = process.env.NEXT_PUBLIC_API_PORT || '8000'; - const voice = (model.includes("marvis") ? "conversational_a" : "af_heart"); + // Determine voice based on model type + let voice = "af_heart"; // default for Kokoro/SparkTTS + if (model.includes("marvis")) { + voice = "conversational_a"; + } else if (model.includes("chatterbox")) { + voice = ""; // Chatterbox uses voice cloning, no preset voice needed + } try { + // Build request body + const requestBody: Record = { + model: model, + input: text, + voice: voice, + speed: speed, + } + + // Add Chatterbox-specific parameters + if (isChatterboxModel(model)) { + requestBody.exaggeration = exaggeration + requestBody.cfg_weight = cfgWeight + requestBody.lang_code = chatterboxLang + if (refAudioBase64) { + requestBody.ref_audio = refAudioBase64 + } + } + + // Add timeout for slow models like Chatterbox (5 minutes) + const controller = new AbortController() + const timeoutMs = isChatterboxModel(model) ? 300000 : 60000 // 5 min for Chatterbox, 1 min for others + const timeoutId = setTimeout(() => controller.abort(), timeoutMs) + const response = await fetch(`${API_BASE_URL}:${API_PORT}/v1/audio/speech`, { method: "POST", headers: { "Content-Type": "application/json", }, - body: JSON.stringify({ - model: model, // Or the specific model identifier if different - input: text, - voice: voice, - speed: speed, - // pitch and other parameters can be added here if supported by the backend - }), + body: JSON.stringify(requestBody), + signal: controller.signal, }) + clearTimeout(timeoutId) + if (!response.ok) { throw new Error(`HTTP error! status: ${response.status}`) } const blob = await response.blob() + setAudioBlob(blob) // Store blob for download const audioUrl = URL.createObjectURL(blob) audioRef.current.src = audioUrl @@ -173,10 +257,7 @@ export default function SpeechSynthesis() { audioRef.current.onended = () => { setIsPlaying(false) setCurrentTime("00:00") - // Revoke the object URL to free up resources - if (audioRef.current?.src.startsWith("blob:")) { - URL.revokeObjectURL(audioRef.current.src) - } + // Don't revoke the blob URL - keep it for potential download } } catch (error) { console.error("Error generating speech:", error) @@ -187,8 +268,20 @@ export default function SpeechSynthesis() { } const handleDownload = () => { - // In a real app, this would download the audio file - alert("Downloading audio...") + if (!audioBlob) { + alert("No audio generated yet. Please generate audio first.") + return + } + + // Create download link from the stored blob + const url = URL.createObjectURL(audioBlob) + const link = document.createElement("a") + link.href = url + link.download = `speech_${Date.now()}.mp3` + document.body.appendChild(link) + link.click() + document.body.removeChild(link) + URL.revokeObjectURL(url) // Clean up after download } const handleFeedback = (isPositive: boolean) => { @@ -231,12 +324,6 @@ export default function SpeechSynthesis() {
-
- -
@@ -327,6 +416,115 @@ export default function SpeechSynthesis() {
)} + {/* Chatterbox-specific controls */} + {isChatterboxModel(baseModel) && ( + <> + {/* Reference Audio Upload */} +
+
+ Reference Audio +
+
+ + + {refAudioFile && ( + + )} +
+

+ Upload a 5-10 second audio clip for voice cloning +

+
+ + {/* Language Selection */} +
+
+ Language +
+ + +
+
+
+ + {/* Exaggeration Slider */} +
+
+ Emotion Exaggeration + {exaggeration.toFixed(2)} +
+
+ 0 + setExaggeration(Number.parseFloat(e.target.value))} + ariaLabel="Emotion exaggeration control" + /> + 1 +
+

+ Controls emotional expressiveness (0.3-0.7 typical) +

+
+ + {/* CFG Weight Slider */} +
+
+ Guidance Weight + {cfgWeight.toFixed(2)} +
+
+ 0 + setCfgWeight(Number.parseFloat(e.target.value))} + ariaLabel="CFG weight control" + /> + 1 +
+

+ Classifier-free guidance strength +

+
+ + )} +
Selected Model: {model} @@ -479,7 +677,7 @@ export default function SpeechSynthesis() {
- {selectedVoice}: {text.length > 20 ? text.substring(0, 20) + "..." : text} + {isChatterboxModel(baseModel) ? (refAudioFile ? refAudioFile.name : "Voice Clone") : selectedVoice}: {text.length > 20 ? text.substring(0, 20) + "..." : text}
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