{"schema":"record/v1","id":"art_01M5MD3YV921NSQHVVFAM9Z64K","type":"article","revision":1,"etag":"\"r1.s0\"","title":"What do the WER and speaker-similarity (SIM) numbers produced by the Seed-TTS-eval scripts actually compute, and what do they not tell me about a generated voice?","summary":"At commit 752f4297 (2024-06-14) seed-tts-eval defines WER as the mean per-utterance word error rate of a Whisper-large-v3 (English) or Paraformer-zh (Mandarin, character-level) transcript against the target text after punctuation stripping, and SIM as the mean cosine similarity between speaker embeddings of the synthesized file and the prompt (reference) audio from a WavLM-large speaker-verification model. Both are proxies: WER measures ASR intelligibility of the text, SIM measures embedding closeness to the prompt clip; neither measures naturalness, prosody, emotion or timing, and the authors themselves say a lower WER can mean more standardized, less characteristic speech. The scripts report only means (no confidence interval) and skip unscorable files.","status":"active","body":{"text":"At commit 752f4297 (2024-06-14) seed-tts-eval defines WER as the mean per-utterance word error rate of a Whisper-large-v3 (English) or Paraformer-zh (Mandarin, character-level) transcript against the target text after punctuation stripping, and SIM as the mean cosine similarity between speaker embeddings of the synthesized file and the prompt (reference) audio from a WavLM-large speaker-verification model. Both are proxies: WER measures ASR intelligibility of the text, SIM measures embedding closeness to the prompt clip; neither measures naturalness, prosody, emotion or timing, and the authors themselves say a lower WER can mean more standardized, less characteristic speech. The scripts report only means (no confidence interval) and skip unscorable files.\n\nCurator qualifications: Code-derived findings were re-derived by reading the same pinned files (not run). Finding 4 holds for both metrics, via different mechanisms: missing generated wavs are dropped when the shared list is built (get_wav_res_ref_text.py), and the SIM loop also skips exceptions and None. Paper Table 1 values and both quotes verified. The rights conflict is confirmed: no root licence (404, metadata null), while the vendored UniSpeech tree carries a CC BY-SA 3.0 text at its root and an MIT (Facebook) text under src/. Rights/verification notes are shown as limitations (L00 0019/ADR-0011): they restrict reuse of the cited material or record what was not verified; they are not cleared by this summary.\n\nLimitations: [component_reuse_restriction] Vendored UniSpeech: which licence applies to which files is undetermined; repository code has no licence (all rights reserved by default).\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://github.com/BytedanceSpeech/seed-tts-eval/blob/752f4297f090c46bb1a55a1f7439e5944ddefe8d/README.md","note":"producer work copy work/seed_run_wer.py (sha256 equals pin; local read); producer work copy work/seed_average_wer.py (sha256 equals pin; local read); producer work copy work/seed_get_wav_res_ref_text.py (sha256 equals pin; local read); producer work copy work/uni_vpl2.py (sha256 equals pin; local read); producer work copy work/uni_average.py (sha256 equals pin; 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