> ## Documentation Index > Fetch the complete documentation index at: https://dragonwingdocs.qualcomm.com/llms.txt > Use this file to discover all available pages before exploring further. # Running the Audio Analytics container > Deploy and run the Audio Analytics container for on-device ASR, text translation, and TTS. Qualcomm's Audio Analytics container exposes speech recognition (ASR), text translation (T2T), and text-to-speech (TTS) through a REST and WebSocket API. All models run fully on-device on the Qualcomm NPU. ## Key features * **Three services in one container**: ASR, text-to-text translation, and TTS exposed through a single API * **NPU-accelerated**: Whisper, OpusMT, MeloTTS, and PiperTTS models all run on the Qualcomm NPU, freeing the CPU for other tasks * **Multilingual**: English, Spanish, and Chinese supported across all three services; German and Italian available via PiperTTS * **Streaming support**: Real-time transcription via WebSocket alongside batch file-based transcription * **OpenAPI / Swagger UI**: Interactive API docs available at `http://:8085/docs` ## Supported models | Service | Model | Languages | Sample Rate | | ----------- | ------------------------------------------------------ | ------------------------- | ----------- | | ASR | `whisper-small-quantized` | English, Spanish, Chinese | 16000 Hz | | Translation | `opus-en-es`, `opus-es-en`, `opus-en-zh`, `opus-zh-en` | English, Spanish, Chinese | n/a | | TTS | `melo-tts-en`, `melo-tts-es`, `melo-tts-zh` | English, Spanish, Chinese | 44100 Hz | | TTS | `piper-tts-en`, `piper-tts-de`, `piper-tts-it` | English, German, Italian | 22050 Hz | These are the currently supported models. Query `/transcriptions/models`, `/translations/models`, and `/tts/models` to confirm which models are loaded at runtime. ## Setup The steps below assume you have already set up your device ([IQ-9075 EVK](/devices/iq9075-evk/set-up-the-device) or [IQ-8275 EVK](/devices/iq8275-evk/set-up-the-device)). Once your device is set up, follow these steps to deploy and run the Audio Analytics container. SSH into your device and install the required packages: ```bash theme={null} sudo apt update sudo apt install curl unzip docker-compose ``` ```bash theme={null} # Configure Docker group sudo groupadd docker sudo usermod -aG docker $USER newgrp docker ``` Create the model directory structure and download all models from QAI Hub. ```bash theme={null} mkdir -p ~/models/audio/asr ~/models/audio/tts ~/models/audio/translation cd ~/models # ASR — Whisper Small curl -L -o whisper_small_quantized.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/whisper_small_quantized/releases/v0.57.0/whisper_small_quantized-voice_ai-w8a16-qualcomm_qcs9075.zip unzip -q whisper_small_quantized.zip -d audio/asr && rm whisper_small_quantized.zip # TTS — MeloTTS (English, Spanish, Chinese) curl -L -o melotts_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/melotts_en/releases/v0.57.0/melotts_en-voice_ai-mixed_with_float-qualcomm_qcs9075.zip unzip -q melotts_en.zip -d audio/tts && rm melotts_en.zip curl -L -o melotts_es.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/melotts_es/releases/v0.57.0/melotts_es-voice_ai-mixed_with_float-qualcomm_qcs9075.zip unzip -q melotts_es.zip -d audio/tts && rm melotts_es.zip curl -L -o melotts_zh.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/melotts_zh/releases/v0.57.0/melotts_zh-voice_ai-mixed_with_float-qualcomm_qcs9075.zip unzip -q melotts_zh.zip -d audio/tts && rm melotts_zh.zip # TTS — PiperTTS (English, German, Italian) curl -L -o pipertts_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pipertts_en/releases/v0.57.0/pipertts_en-voice_ai-float-qualcomm_qcs9075.zip unzip -q pipertts_en.zip -d audio/tts && rm pipertts_en.zip curl -L -o pipertts_de.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pipertts_de/releases/v0.57.0/pipertts_de-voice_ai-float-qualcomm_qcs9075.zip unzip -q pipertts_de.zip -d audio/tts && rm pipertts_de.zip curl -L -o pipertts_it.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pipertts_it/releases/v0.57.0/pipertts_it-voice_ai-float-qualcomm_qcs9075.zip unzip -q pipertts_it.zip -d audio/tts && rm pipertts_it.zip # Translation — Opus (English ↔ Spanish, English ↔ Chinese) curl -L -o opus_mt_en_es.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_en_es/releases/v0.57.0/opus_mt_en_es-voice_ai-float-qualcomm_qcs9075.zip unzip -q opus_mt_en_es.zip -d audio/translation && rm opus_mt_en_es.zip curl -L -o opus_mt_es_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_es_en/releases/v0.57.0/opus_mt_es_en-voice_ai-float-qualcomm_qcs9075.zip unzip -q opus_mt_es_en.zip -d audio/translation && rm opus_mt_es_en.zip curl -L -o opus_mt_en_zh.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_en_zh/releases/v0.57.0/opus_mt_en_zh-voice_ai-float-qualcomm_qcs9075.zip unzip -q opus_mt_en_zh.zip -d audio/translation && rm opus_mt_en_zh.zip curl -L -o opus_mt_zh_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_zh_en/releases/v0.57.0/opus_mt_zh_en-voice_ai-float-qualcomm_qcs9075.zip unzip -q opus_mt_zh_en.zip -d audio/translation && rm opus_mt_zh_en.zip ``` ```bash theme={null} mkdir -p ~/models/audio/asr ~/models/audio/tts ~/models/audio/translation cd ~/models # ASR — Whisper Small curl -L -o whisper_small_quantized.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/whisper_small_quantized/releases/v0.57.0/whisper_small_quantized-voice_ai-w8a16-qualcomm_qcs8275.zip unzip -q whisper_small_quantized.zip -d audio/asr && rm whisper_small_quantized.zip # TTS — MeloTTS (English, Spanish, Chinese) curl -L -o melotts_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/melotts_en/releases/v0.57.0/melotts_en-voice_ai-mixed_with_float-qualcomm_qcs8275.zip unzip -q melotts_en.zip -d audio/tts && rm melotts_en.zip curl -L -o melotts_es.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/melotts_es/releases/v0.57.0/melotts_es-voice_ai-mixed_with_float-qualcomm_qcs8275.zip unzip -q melotts_es.zip -d audio/tts && rm melotts_es.zip curl -L -o melotts_zh.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/melotts_zh/releases/v0.57.0/melotts_zh-voice_ai-mixed_with_float-qualcomm_qcs8275.zip unzip -q melotts_zh.zip -d audio/tts && rm melotts_zh.zip # TTS — PiperTTS (English, German, Italian) curl -L -o pipertts_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pipertts_en/releases/v0.57.0/pipertts_en-voice_ai-float-qualcomm_qcs8275.zip unzip -q pipertts_en.zip -d audio/tts && rm pipertts_en.zip curl -L -o pipertts_de.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pipertts_de/releases/v0.57.0/pipertts_de-voice_ai-float-qualcomm_qcs8275.zip unzip -q pipertts_de.zip -d audio/tts && rm pipertts_de.zip curl -L -o pipertts_it.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/pipertts_it/releases/v0.57.0/pipertts_it-voice_ai-float-qualcomm_qcs8275.zip unzip -q pipertts_it.zip -d audio/tts && rm pipertts_it.zip # Translation — Opus (English ↔ Spanish, English ↔ Chinese) curl -L -o opus_mt_en_es.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_en_es/releases/v0.57.0/opus_mt_en_es-voice_ai-float-qualcomm_qcs8275.zip unzip -q opus_mt_en_es.zip -d audio/translation && rm opus_mt_en_es.zip curl -L -o opus_mt_es_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_es_en/releases/v0.57.0/opus_mt_es_en-voice_ai-float-qualcomm_qcs8275.zip unzip -q opus_mt_es_en.zip -d audio/translation && rm opus_mt_es_en.zip curl -L -o opus_mt_en_zh.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_en_zh/releases/v0.57.0/opus_mt_en_zh-voice_ai-float-qualcomm_qcs8275.zip unzip -q opus_mt_en_zh.zip -d audio/translation && rm opus_mt_en_zh.zip curl -L -o opus_mt_zh_en.zip \ https://qaihub-public-assets.s3.us-west-2.amazonaws.com/qai-hub-models/models/opus_mt_zh_en/releases/v0.57.0/opus_mt_zh_en-voice_ai-float-qualcomm_qcs8275.zip unzip -q opus_mt_zh_en.zip -d audio/translation && rm opus_mt_zh_en.zip ``` Your models directory should now look like this: ``` ~/models/audio/ ├── asr/ ← whisper_small_quantized ├── tts/ ← melotts_en, melotts_es, melotts_zh, pipertts_en, pipertts_de, pipertts_it └── translation/ ← opus_mt_en_es, opus_mt_es_en, opus_mt_en_zh, opus_mt_zh_en ``` Download the Docker Compose file for your device from the [CodeLinaro audio-analytics deploy directory](https://git.codelinaro.org/clo/iot-solutions-microservices/audio-analytics/-/tree/main/deploy). **Option A — download directly on the device:** ```bash theme={null} curl -L -o docker-compose-qcs9100.yml \ https://git.codelinaro.org/clo/iot-solutions-microservices/audio-analytics/-/raw/main/deploy/docker-compose-qcs9100.yml ``` **Option B — download locally and copy to the device:** ```bash theme={null} scp docker-compose-qcs9100.yml ubuntu@:~/ ``` **Option A — download directly on the device:** ```bash theme={null} curl -L -o docker-compose-qcs8300.yml \ https://git.codelinaro.org/clo/iot-solutions-microservices/audio-analytics/-/raw/main/deploy/docker-compose-qcs8300.yml ``` **Option B — download locally and copy to the device:** ```bash theme={null} scp docker-compose-qcs8300.yml ubuntu@:~/ ``` The remaining steps use `docker-compose-qcs9100.yml`. If you are on the IQ-8275 EVK, substitute `docker-compose-qcs8300.yml` in each command. Open the Docker Compose file and adjust the following environment variables as needed: * **`MODELS_DIR`**: Base path for all models inside the container (default: `/mnt/work/models`) * **`SESSION_TIMEOUT_S`**: Seconds of inactivity before an ASR streaming session is automatically closed (default: `30`) * **`LOG_LEVEL`**: `10`=DEBUG, `20`=INFO, `30`=WARNING, `40`=ERROR (default: `20`) Under `volumes:` * **Model path**: By default maps `~/models/audio` on the host to `/mnt/work/models` in the container. If you placed your models elsewhere, update the left side of the volume mount: ```yaml theme={null} volumes: - ~/models/audio:/mnt/work/models:ro ``` Make sure the volume mount points to your models directory and that the directory is readable by the container. If models fail to load, check directory permissions with `ls -la ~/models/audio`. The Docker Compose file pulls the container image automatically if it isn't already present. ```bash theme={null} docker compose -f docker-compose-qcs9100.yml up -d ``` Verify the container is running: ```bash theme={null} docker ps | grep audio-analytics ``` Once ready, check the health endpoint: ```bash theme={null} curl http://localhost:8085/audio-analytics/v1/api/health ``` Expected response: ```json theme={null} { "status": "ok", "uptime": 12345, "active_sessions": 0, "version": "1.0.0" } ``` You can also confirm which models are loaded: ```bash theme={null} curl http://localhost:8085/audio-analytics/v1/api/transcriptions/models curl http://localhost:8085/audio-analytics/v1/api/translations/models curl http://localhost:8085/audio-analytics/v1/api/tts/models ``` Run a quick smoke test for each of the three services. **ASR — transcribe audio:** ```bash theme={null} curl -X POST http://localhost:8085/audio-analytics/v1/api/transcriptions/create \ -F 'file=@audio.wav' \ -F 'model=whisper-small-quantized' \ -F 'language=en' \ -F 'stream=false' ``` Expected response: ```json theme={null} { "text": "Your transcribed text here.", "language": "en", "type": "transcript.text.done" } ``` **Translation — translate text:** ```bash theme={null} curl -X POST http://localhost:8085/audio-analytics/v1/api/translations/translate \ -H 'Content-Type: application/json' \ -d '{"text": ["Hello world"], "model": "opus-en-es", "source_language": "en", "target_language": "es"}' ``` Expected response: ```json theme={null} { "translations": [{ "translated_text": "Hola mundo", "source_language": "en", "target_language": "es" }] } ``` **TTS — synthesize speech:** ```bash theme={null} curl -X POST http://localhost:8085/audio-analytics/v1/api/tts/synthesize \ -H 'Content-Type: application/json' \ -d '{"text": "Hello, how are you today?", "model": "melo-tts-en", "language": "en", "sample_rate": 44100}' \ --output speech.pcm ``` When you are finished: ```bash theme={null} docker compose -f docker-compose-qcs9100.yml down ``` ## Viewing logs All container output is available via `docker logs`. There are no separate log files. ```bash theme={null} # Stream all logs docker logs audio-analytics -f -t ``` To adjust log verbosity, set `LOG_LEVEL` in your Docker Compose file and restart the container: | Value | Level | | ----- | -------------- | | `10` | DEBUG | | `20` | INFO (default) | | `30` | WARNING | | `40` | ERROR | ## Next steps File-based and real-time streaming transcription Synthesize natural speech in multiple languages Translate text between languages on-device