Upload app.py

app.py

@@ -126,6 +126,10 @@ CHOICES = {
     '🇯🇵 🚺 Japanese Female 0': 'jf_0',
 }
 VOICES = {k: torch.load(os.path.join(snapshot, 'voices', f'{k}.pt'), weights_only=True).to(device) for k in CHOICES.values()}
+def get_random_en_voice():
+    # Top 2 most stable voices in each category of (US/GB) and (F/M)
+    # excluding Adam, because he is too recognizable
+    return random.choice(['af_0', 'af_bella', 'am_michael', 'bf_0', 'bf_2', 'bm_0', 'bm_1'])
 
 np_log_99 = np.log(99)
 def s_curve(p):
@@ -165,7 +169,9 @@ def forward(tokens, voice, speed):
     asr = t_en @ pred_aln_trg.unsqueeze(0).to(device)
     return model.decoder(asr, F0_pred, N_pred, ref_s[:, :128]).squeeze().cpu().numpy()
 
-def generate(text, voice, ps=None, speed=1.0, reduce_noise=0.5, opening_cut=4000, closing_cut=2000, ease_in=3000, ease_out=1000, pad_before=5000, pad_after=5000):
+def generate(text, voice=None, ps=None, speed=1.0, reduce_noise=0.5, opening_cut=4000, closing_cut=2000, ease_in=3000, ease_out=1000, pad_before=5000, pad_after=5000):
+    if voice not in VOICES:
+        voice = get_random_en_voice()
     ps = ps or phonemize(text, voice)
     tokens = tokenize(ps)
     if not tokens: