BALENA is a voice interaction framework utilizing state-of-the-art natural language processing and audio processing models to create a system that can interpret voice commands and associate them with predefined actions. The framework leverages the power of transformers and signal processing to understand user intent via spoken language and correlates them with a series of predefined actionable responses.
Features
- Real-time audio streaming and recording: Record audio from the microphone in real time for processing.
- Speech recognition with Wav2Vec 2.0: Use a pre-trained Wav2Vec 2.0 model to convert speech to text.
- Text similarity and action triggering: Encode the transcribed text to a vector space and find the closest action using sentence similarity techniques.
- High-pass filtering: Process the audio signal with a high-pass filter to enhance signal quality.
- Auto-correction: Utilize the Jaccard distance to correct words in the transcribed text auto-magically.
- Framework flexibility: Support for different device execution contexts, allowing for usage on both CPU and CUDA devices.
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[ 0.63 ms ] story [ 13.9 ms ] thread- Real-time audio streaming and recording: Record audio from the microphone in real time for processing. - Speech recognition with Wav2Vec 2.0: Use a pre-trained Wav2Vec 2.0 model to convert speech to text. - Text similarity and action triggering: Encode the transcribed text to a vector space and find the closest action using sentence similarity techniques. - High-pass filtering: Process the audio signal with a high-pass filter to enhance signal quality. - Auto-correction: Utilize the Jaccard distance to correct words in the transcribed text auto-magically. - Framework flexibility: Support for different device execution contexts, allowing for usage on both CPU and CUDA devices.