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fix: revert to native routing for 300M series, fix base model babbling

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Hawk Lee
2026-01-01 01:03:51 +08:00
parent 66bee30afa
commit 107405f8db
1 changed files with 11 additions and 13 deletions
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aiia_cosyvoice_nodes.py
+11 -13
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@@ -597,8 +597,9 @@ class AIIA_CosyVoice_TTS:
e_eng = emotion_map.get(emotion_core)
# Prefix gender hint to fix the "always female" bug in V1 Instruct
# Even with the embedding patch, text hints help the LLM align.
gender_prefix = "A mature male speaker" if base_gender == "Male" else "A sweet female speaker"
# Note: Official Instruct model deletes embedding, so text hints are the ONLY control.
# English hints seem more effective for gender.
gender_prefix = "A male speaker" if base_gender == "Male" else "A female speaker"
if d_eng and e_eng: parts.append(f"{gender_prefix} with a {d_eng} in a {e_eng} mood.")
elif d_eng: parts.append(f"{gender_prefix} with a {d_eng}.")
@@ -656,12 +657,12 @@ class AIIA_CosyVoice_TTS:
raise ValueError(f"Speaker ID '{spk_id}' not found. Available: {available_spks if available_spks else 'None (Zero-Shot model)'}")
elif reference_audio is None:
# --- V1 (300M) Special Handling for Gender ---
if not is_v3 and not is_v2 and (is_instruct or is_base) and base_gender in ["Male", "Female"]:
# Force Zero-Shot fallback for Instruct/Base models to ensure deep male voice.
# As discovered in audit, Instruct model built-in IDs can be female-biased.
if not is_v3 and not is_v2 and is_base and base_gender in ["Male", "Female"]:
# Force Zero-Shot fallback ONLY for Base models (since they have no native Instruct/SFT gender support).
use_seed_fallback = True
print(f"[AIIA] V1 { 'Instruct' if is_instruct else 'Base' } detected. Forcing Zero-Shot fallback for {base_gender} stability.")
print(f"[AIIA] V1 Base detected. Forcing Zero-Shot fallback for {base_gender} stability.")
# Instruct and SFT models go through normal speaker selection
elif available_spks:
# SFT mode path or confirmed good IDs
# Improve auto-selection based on base_gender
@@ -764,13 +765,10 @@ class AIIA_CosyVoice_TTS:
p_text = "希望你以后能够做的比我还好呦。"
if not is_v3 and not is_v2: # V1 Zero-Shot path
if final_instruct:
# Prepend instruction to seed transcript for Hybrid Instruct support
p_text = f"{final_instruct} {p_text}"
print(f"[AIIA] V1 Hybrid Instruct set: {p_text[:80]}...")
# Clear effective_spk to ensure zero_shot doesn't use SFT logic later
# But we need its ID for inference_zero_shot signature if we use high-level AutoModel (which we don't here)
# effective_spk is used as spk_id placeholder in seed logic below
# CRITICAL: Base models MUST NOT have instructions in the transcript
# It causes babbling/hallucination.
pass
output = cosyvoice_model.inference_zero_shot(tts_text=tts_text, prompt_text=p_text, prompt_wav=ref_path, stream=False, speed=speed)
all_speech = [chunk['tts_speech'] for chunk in output]