Update app.py

app.py

@@ -1,80 +1,192 @@
 import io
+import os
+import tempfile
 from datetime import datetime
-from gtts import gTTS
+
+import librosa
+import numpy as np
+import soundfile as sf
 import streamlit as st
+from TTS.api import TTS
+
+st.set_page_config(page_title="Urdu Voice Cloner", page_icon="🗣️", layout="centered")
 
-st.set_page_config(page_title="Urdu Voice Over", page_icon="🔊", layout="centered")
+st.title("🗣️ Urdu Text → Your Voice (Voice Cloning)")
+st.caption("Upload a short sample of your voice, type Urdu text, and get audio in your voice.")
 
-st.title("🔊 Urdu Text → Voice")
-st.caption("Type or paste Urdu text and get an MP3 voice over. Works great on Hugging Face Spaces.")
+# ----------------------------
+# Caching the model to avoid reloading
+# ----------------------------
+@st.cache_resource(show_spinner=True)
+def load_tts():
+    # XTTS v2 supports multilingual zero-shot cloning, including Urdu (code: 'ur')
+    # Model will download on first run and then be cached by the Space
+    return TTS(model_name="tts_models/multilingual/multi-dataset/xtts_v2")
 
-# Sidebar options
+tts = load_tts()
+
+# ----------------------------
+# Sidebar: options
+# ----------------------------
 with st.sidebar:
     st.header("Options")
-    slow = st.checkbox("Slow reading", False)
-    file_basename = st.text_input("Output filename (without extension)", "urdu_voice")
+    st.markdown("**Reference voice**")
+    st.caption("Upload a clean 10–30 second sample with minimal noise.")
+    # XTTS controls
+    similarity_boost = st.slider("Similarity boost", 0.0, 1.0, 0.75, 0.05)
+    stability = st.slider("Stability", 0.0, 1.0, 0.6, 0.05)
+    style = st.slider("Style (expressiveness)", 0.0, 1.0, 0.35, 0.05)
+    seed = st.number_input("Random seed (for reproducibility)", value=42, step=1)
+
     st.markdown("---")
-    st.write("Tips")
-    st.caption("1) Paste clean Urdu text\n2) Use Slow reading if the voice feels fast\n3) Download the MP3 for editing")
+    st.markdown("**Post-processing**")
+    rate = st.slider("Speaking rate (time-stretch)", 0.75, 1.25, 1.00, 0.01)
+    normalize = st.checkbox("Normalize loudness", True)
 
-# Main input
-default_sample = "یہ ایک سادہ مثال ہے، آپ یہاں اپنا متن لکھیں اور آڈیو حاصل کریں۔"
+    st.markdown("---")
+    base_name = st.text_input("Output filename (no extension)", "urdu_voice_clone")
+
+# ----------------------------
+# Inputs
+# ----------------------------
+ref_file = st.file_uploader(
+    "Upload your voice sample (wav/mp3/m4a)", 
+    type=["wav", "mp3", "m4a", "ogg", "flac"]
+)
+
+default_text = "یہ میری آواز کی مثال ہے۔ آپ یہاں اپنا متن لکھیں اور آڈیو حاصل کریں۔"
 text = st.text_area(
     "Urdu text",
-    value=default_sample,
-    height=200,
+    value=default_text,
+    height=180,
     placeholder="یہاں اردو میں ٹیکسٹ لکھیں یا پیسٹ کریں…"
 )
 
-def tts_to_bytes(urdu_text: str, slow_read: bool = False) -> bytes:
-    # gTTS automatically chunks long text
-    tts = gTTS(text=urdu_text, lang="ur", slow=slow_read)
-    buf = io.BytesIO()
-    tts.write_to_fp(buf)
-    buf.seek(0)
-    return buf.read()
-
-col1, col2 = st.columns([1,1])
+col1, col2 = st.columns(2)
 with col1:
-    make_audio = st.button("🎙️ Generate Voice", use_container_width=True)
+    run_btn = st.button("🎙️ Generate", use_container_width=True)
 with col2:
-    clear = st.button("🧹 Clear", use_container_width=True)
+    clear_btn = st.button("🧹 Clear", use_container_width=True)
 
-if clear:
+if clear_btn:
     st.session_state.pop("audio_bytes", None)
-    st.session_state.pop("last_text", None)
+    st.session_state.pop("preview_sr", None)
     st.experimental_rerun()
 
-if make_audio:
+# ----------------------------
+# Helpers
+# ----------------------------
+def load_and_standardize(audio_file, target_sr=16000):
+    """Load user audio, convert to mono 16 kHz WAV bytes and return temp path."""
+    y, sr = librosa.load(audio_file, sr=None, mono=True)
+    if len(y) < target_sr * 3:
+        st.warning("Voice sample is very short. Try at least 5–10 seconds for better cloning.")
+    y_res = librosa.resample(y, orig_sr=sr, target_sr=target_sr)
+    # Light trim to remove leading/trailing silence
+    yt, _ = librosa.effects.trim(y_res, top_db=30)
+    if yt.size < target_sr:  # ensure at least 1s remains
+        yt = y_res
+    tmp_wav = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
+    sf.write(tmp_wav.name, yt, target_sr)
+    return tmp_wav.name
+
+def postprocess_rate_and_norm(wav, sr, rate_factor=1.0, do_norm=True):
+    """Time-stretch and normalize loudness."""
+    y = wav.astype(np.float32)
+    if rate_factor != 1.0:
+        # librosa requires strictly positive values
+        y = librosa.effects.time_stretch(y, rate_factor)
+    if do_norm:
+        peak = np.max(np.abs(y)) + 1e-9
+        y = 0.98 * (y / peak)
+    return y
+
+def wav_bytes_from_array(y, sr):
+    buf = io.BytesIO()
+    sf.write(buf, y, sr, format="WAV")
+    buf.seek(0)
+    return buf.read()
+
+# ----------------------------
+# Run
+# ----------------------------
+if run_btn:
     if not text.strip():
-        st.warning("براہ کرم آڈیو بنانے کے لیے اردو متن درج کریں")
+        st.warning("براہ کرم اردو متن درج کریں۔")
+    elif ref_file is None:
+        st.warning("براہ کرم اپنی آواز کی آڈیو فائل اپلوڈ کریں۔")
     else:
         try:
-            audio_bytes = tts_to_bytes(text.strip(), slow_read=slow)
+            st.info("Preparing reference voice…")
+            ref_path = load_and_standardize(ref_file)
+
+            st.info("Cloning voice and synthesizing Urdu…")
+            # Generate to a temporary file first
+            out_wav_path = tempfile.NamedTemporaryFile(delete=False, suffix=".wav").name
+
+            # Coqui XTTS generation
+            # Extra params passed via "speaker_wav" and "language"
+            # Controls: "speaker_similarity", "style", "temperature", "length_scale" etc. are model dependent.
+            tts.tts_to_file(
+                text=text.strip(),
+                file_path=out_wav_path,
+                speaker_wav=ref_path,
+                language="ur",
+                # Extra inference kwargs routed to the model (supported by XTTS v2)
+                # See: https://github.com/coqui-ai/TTS
+                # Using similarity/stability/style through speaker conditioning
+                # Some builds accept these as speaker_cfg; we forward common names:
+                split_sentences=True,
+                speed=1.0,  # base speed, we will also post-process rate
+                speaker_similarity=similarity_boost,
+                stability=stability,
+                style_wav=None,
+                style=style,
+                seed=int(seed)
+            )
+
+            # Read back and post-process
+            y, sr = sf.read(out_wav_path, dtype="float32")
+            y = postprocess_rate_and_norm(y, sr, rate_factor=rate, do_norm=normalize)
+            audio_bytes = wav_bytes_from_array(y, sr)
+
+            # Stash in session for preview and download
             st.session_state["audio_bytes"] = audio_bytes
-            st.session_state["last_text"] = text.strip()
-            st.success("آڈیو تیار ہے")
+            st.session_state["preview_sr"] = sr
+
+            # Clean temp files
+            try:
+                os.remove(ref_path)
+                os.remove(out_wav_path)
+            except Exception:
+                pass
+
+            st.success("آڈیو تیار ہے۔ نیچے سنیں یا ڈاؤن لوڈ کریں۔")
+
         except Exception as e:
             st.error(f"کچھ مسئلہ آیا: {e}")
 
-# Playback and download
+# ----------------------------
+# Preview and download
+# ----------------------------
 if "audio_bytes" in st.session_state:
     st.markdown("### ▶️ Preview")
-    st.audio(st.session_state["audio_bytes"], format="audio/mp3")
+    st.audio(st.session_state["audio_bytes"], format="audio/wav")
 
-    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-    base = file_basename.strip() or "urdu_voice"
-    fname = f"{base}_{timestamp}.mp3"
+    ts = datetime.now().strftime("%Y%m%d_%H%M%S")
+    base = (base_name or "urdu_voice_clone").strip()
+    fname = f"{base}_{ts}.wav"
 
     st.download_button(
-        label="⬇️ Download MP3",
+        "⬇️ Download WAV",
         data=st.session_state["audio_bytes"],
         file_name=fname,
-        mime="audio/mpeg",
+        mime="audio/wav",
         use_container_width=True
     )
 
 st.markdown("---")
 st.caption(
-    "Note: This app uses gTTS for Urdu speech synthesis. If your Space is very busy or internet is restricted, synthesis can fail. Try again after a short while."
+    "Tips: Use a clear 10–30 second reference with low noise. Speak naturally. "
+    "If cloning feels off, try a different sample, raise Similarity, or lower Stability a little."
 )