Evaluating Phonon: how we made the best TTS model for edge devices
Blog post from Gradium
Phonon is Gradium's on-device text-to-speech (TTS) model, notable for its compact size of approximately 100 million parameters and its ability to run efficiently on a single CPU core, making it suitable for mobile devices and browser applications without requiring GPU acceleration. In evaluations using the Seed-TTS English benchmark, Phonon achieved a word error rate (WER) of 1.48% and a speaker similarity of 56.37%, outperforming larger models like Kani-TTS2 and NeuTTS Air. The model supports voice cloning from a 10-second sample, allowing it to replicate the tone, accent, and cadence of the reference speaker without needing a transcription of the reference audio. By leveraging efficient audio language models, Phonon offers high-fidelity text-to-speech capabilities, making it applicable for various uses, such as accessibility apps preserving user voices, language learning tools maintaining consistent teacher voices, and consumer apps offering diverse voice styles. The evaluation process for Phonon involves transcribing generated speech back to text to compute WER and using speaker embeddings to measure speaker similarity, with the model currently in private beta and under active development for further improvements.
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