facebookresearch/fairseq

Evaluating TTS using STT

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#5,629 建立於 2025年7月19日

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enhancementhelp wantedneeds triage

描述

I tried to get a text back from the speech I generated using this model, but the text was a bit of. So maybe having some type of test could help while improving the model.

Basically, "some text" -> speech output -> speech input -> text output -> check if text output is "some text"

貢獻者指南

技術棧
python
領域
machine learningaitesting
議題類型
test
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
4
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
1-3 hours
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
fresh
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
unclear
前置要求
basic knowledge of fairseqfamiliarity with TTS and STT models
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
30
研究方向
The issue proposes a cyclical evaluation for TTS models: convert text to speech using the model, then transcribe the speech back to text using an STT model, and compare the output text to the input. To implement this, a contributor should first explore if fairseq already has any evaluation scripts or example notebooks. They could also look into integrating an off the shelf STT model like wav2vec 2.0 or Whisper. The main steps would be: (1) generate speech from a set of test texts using the existing TTS model, (2) pass the audio through an STT model, (3) compute metrics like WER or CER. The contributor should also check existing issues or PRs for similar work.