- name
- willow-inference-server
- description
- Local ASR and TTS inference server. Use when the user wants to transcribe audio to text (ASR) or convert text to speech (TTS). Requires a running Willow Inference Server instance. Supports Whisper for ASR and custom TTS voices.
- metadata
- {}
Willow Inference Server Skill
Local ASR (speech-to-text) and TTS (text-to-speech) inference server.
Setup
1. Start Willow Inference Server
git clone https://github.com/toverainc/willow-inference-server.git
cd willow-inference-server
./utils.sh install
./utils.sh gen-cert your-hostname
./utils.sh runServer runs at https://your-hostname:19000
2. Configure Environment
Set the server URL:
export WILLOW_BASE_URL="https://your-hostname:19000"Or configure per request (see below).
ASR (Speech-to-Text)
Transcribe Audio File
curl -X POST "${WILLOW_BASE_URL}/api/asr" \
-F "audio_file=@/path/to/audio.m4a" \
-F "language=auto"Parameters
| Parameter | Description | Default |
|---|---|---|
| audio_file | Audio file to transcribe | required |
| language | Language code (en, zh, etc.) or "auto" | auto |
| model | Whisper model (tiny, base, medium, large-v2) | server config |
| task | transcribe or translate | transcribe |
Supported Formats
- MP3, WAV, M4A, OGG, FLAC, WebM
Example: Transcribe with curl
# Basic transcription
curl -X POST "${WILLOW_BASE_URL}/asr" \
-F "audio_file=@recording.m4a" \
-F "language=zh"
# With specific model
curl -X POST "${WILLOW_BASE_URL}/asr" \
-F "audio_file=@meeting.mp3" \
-F "language=en" \
-F "model=base"TTS (Text-to-Speech)
Convert Text to Speech
curl -X POST "${WILLOW_BASE_URL}/tts" \
-H "Content-Type: application/json" \
-d '{"text": "Hello world", "voice": "af_sarah"}'Parameters
| Parameter | Description | Default |
|---|---|---|
| text | Text to convert to speech | required |
| voice | Voice ID (see below) | default voice |
| speed | Speech speed (0.5-2.0) | 1.0 |
| volume | Volume (0.0-1.0) | 1.0 |
Available Voices
Common voices (format: gender_voicename):
af_sarah- Sarah (Female)af_bella- Bella (Female)am_michael- Michael (Male)am_alex- Alex (Male)
Check server docs for full list: ${WILLOW_BASE_URL}/api/docs
Example: TTS with curl
# Basic TTS
curl -X POST "${WILLOW_BASE_URL}/tts" \
-H "Content-Type: application/json" \
-d '{"text": "你好，这是测试"}' \
-o output.wav
# With custom voice
curl -X POST "${WILLOW_BASE_URL}/tts" \
-H "Content-Type: application/json" \
-d '{"text": "Hello!", "voice": "am_michael", "speed": 1.2}' \
-o hello.mp3Environment Variables
| Variable | Description | Default |
|---|---|---|
| WILLOW_BASE_URL | Server URL | https://localhost:19000 |
Workflow Examples
1. Record and Transcribe
# Record audio (macOS)
rec test.wav
# Transcribe
curl -X POST "${WILLOW_BASE_URL}/asr" \
-F "audio_file=@test.wav" \
-F "language=auto"2. Text to Speech
# Convert text to speech
curl -X POST "${WILLOW_BASE_URL}/tts" \
-H "Content-Type: application/json" \
-d '{"text": "今天的任务是学习新技能"}' \
-o speech.wav3. Batch Transcription
for f in *.m4a; do
curl -X POST "${WILLOW_BASE_URL}/asr" \
-F "audio_file=@$f" \
-F "language=auto" \
-o "${f%.m4a}.txt"
doneAPI Documentation
Full API docs available at: ${WILLOW_BASE_URL}/api/docs
Notes
- All endpoints require HTTPS (or HTTP if configured)
- Audio files are processed locally on the server
- ASR latency depends on model size and hardware
- TTS voices can be customized with custom voice recordings