Vikhrmodels/salt-qwen2.5-0.5b-asr-tts

Model Performance Overview

Metrics:

• PESQ: Perceptual Evaluation of Speech Quality (higher = better).
• STOI: Short-Time Objective Intelligibility (closer to 1 = better).
• SI-SDR: Scale-Invariant Signal-to-Distortion Ratio (higher = better).

Model	PESQ@200	STOI@200	SI-SDR@200
Fish-aduio-1.5	1.20	0.16	23.0
SALT-tts	1.11	0.16	23.58
SALT-tts+asr	1.09	0.18	23.09

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Our Solution

• Method: Extends a pre-trained LLM with audio tokens and fine-tunes on TTS and ASR tasks.
• Training:
  • BigCodec tokenizer (supports Slavic languages) for speech generation.
  • SpeechTokenizer (semantic tokens only) for speech recognition.
  • Training time: 168 H100 GPU hours.
• Advantages: Unified LM loss for dual tasks, minimal training overhead.

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Resources

• Code: GitHub Repo

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