Offline Speech Recognition and Synthesis on Raspberry Pi

A local speech pipeline

A device can capture audio, detect speech, transcribe an utterance, choose a response and synthesize speech without sending every recording to a remote service. This can improve offline availability and provide a clearer privacy boundary, although model files and updates still need lifecycle management.

Text to speech with Piper

Piper uses local voice models to synthesize audio. Integration should validate the voice model’s language, license, sampling rate and memory footprint. Stream generated audio when responsiveness matters instead of waiting for the entire utterance.

Speech to text with Vosk

Vosk provides offline recognition models and a streaming API. Audio input must match the recognizer configuration, and vocabulary or grammar constraints can help in command-oriented use cases. Evaluate Vietnamese and English separately with recordings from the intended microphones and acoustic environment.

Integrating listening, recognition and response

• Use voice-activity detection to decide when an utterance begins and ends.
• Keep an explicit state machine for listening, processing, speaking and interruption.
• Provide visual or audible feedback when the microphone is active.
• Measure word errors and command success across speakers and noise conditions.