Update tts.py

tts.py

@@ -1,96 +1,98 @@
-from TTS.api import TTS
-from pydub import AudioSegment
-import os
-import re
-import ffmpeg
-import shutil
-import argparse
-
-def adjust_speed(input_file, speed_factor):
-    output_file = input_file.replace(".wav", "_adjusted.wav")
-    ffmpeg.input(input_file).filter('atempo', speed_factor).output(output_file, acodec='pcm_s16le').run()
-    return output_file
-
-def generate_speech(text, speaker_voice_map, output_file):
-    combined_audio = AudioSegment.empty()
-    temp_files = []
-
-    tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to("cuda")
-
-    for line in text.split("\n"):
-        if not line.strip():
-            continue
-
-        match = re.match(r"\[SPEAKER_(\d+)\] \[(\d+\.\d+)-(\d+\.\d+)\] (.+)", line)
-        if not match:
-            continue
-
-        speaker_id, start_time, end_time, sentence = match.groups()
-        start_time, end_time = float(start_time), float(end_time)
-        segment_duration = (end_time - start_time) * 1000  # Duration in milliseconds
-
-        speaker_wav = speaker_voice_map.get(f"SPEAKER_{speaker_id}")
-        if not speaker_wav:
-            continue
-
-        os.makedirs('./audio/temp', exist_ok=True)
-        temp_file_path = f"./audio/temp/temp_output_part_{len(temp_files)}.wav"
-        temp_files.append(temp_file_path)
-
-        tts_speed = 1.0
-        tts.tts_to_file(text=sentence, file_path=temp_file_path, speaker_wav=speaker_wav, language="es", speed=tts_speed)
-
-        segment_audio = AudioSegment.from_wav(temp_file_path)
-
-        if segment_audio.duration_seconds * 1000 > segment_duration:
-            while tts_speed < 2.0 and segment_audio.duration_seconds * 1000 > segment_duration:
-                tts_speed += 0.5
-                tts.tts_to_file(text=sentence, file_path=temp_file_path, speaker_wav=speaker_wav, language="es", speed=tts_speed)
-                segment_audio = AudioSegment.from_wav(temp_file_path)
-
-            if segment_audio.duration_seconds * 1000 > segment_duration:
-                required_speed = segment_duration / (segment_audio.duration_seconds * 1000)
-                if required_speed < 1.0:
-                    required_speed = 1.0 / required_speed
-                temp_file_path = adjust_speed(temp_file_path, required_speed)
-                segment_audio = AudioSegment.from_wav(temp_file_path)
-
-        if combined_audio.duration_seconds == 0 and start_time > 0:
-            combined_audio = AudioSegment.silent(duration=start_time * 1000) + combined_audio
-
-        if segment_audio.duration_seconds * 1000 > segment_duration:
-            segment_audio = segment_audio[:segment_duration]
-        else:
-            segment_audio = segment_audio + AudioSegment.silent(duration=segment_duration - len(segment_audio))
-
-        combined_audio += segment_audio
-
-    combined_audio.export(output_file, format="wav")
-
-    for temp_file in temp_files:
-        os.remove(temp_file)
-
-def map_speaker_ids(directory):
-    speaker_voice_map = {}
-    for file in os.listdir(directory):
-        if file.endswith(".wav"):
-            speaker_id = file.replace(".wav", "")
-            speaker_voice_map[speaker_id] = os.path.join(directory, file)
-    return speaker_voice_map
-
-def main(speaker_directory, aligned_text_file, output_audio_file):
-    speaker_voice_map = map_speaker_ids(speaker_directory)
-    with open(aligned_text_file, 'r') as file:
-        translated_text = file.read()
-    generate_speech(translated_text, speaker_voice_map, output_audio_file)
-    if os.path.exists('./audio/temp'):
-        shutil.rmtree('./audio/temp')
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Generate speech from translated text")
-    parser.add_argument("speaker_directory", help="Directory containing speaker voice clips")
-    parser.add_argument("aligned_text_file", help="Path to the translated and aligned text file")
-    parser.add_argument("output_audio_file", help="Path to save the generated speech audio file")
-    args = parser.parse_args()
-
-    main(args.speaker_directory, args.aligned_text_file, args.output_audio_file)
+from TTS.api import TTS
+from pydub import AudioSegment
+import os
+import re
+import ffmpeg
+import shutil
+import argparse
+
+def adjust_speed(input_file, speed_factor):
+    output_file = input_file.replace(".wav", "_adjusted.wav")
+    ffmpeg.input(input_file).filter('atempo', speed_factor).output(output_file, acodec='pcm_s16le').run()
+    return output_file
+
+def generate_speech(text, speaker_voice_map, output_file):
+    combined_audio = AudioSegment.empty()
+    temp_files = []
+
+    tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2").to("cuda")
+
+    for line in text.split("\n"):
+        if not line.strip():
+            continue
+
+        match = re.match(r"\[SPEAKER_(\d+)\] \[(\d+\.\d+)-(\d+\.\d+)\] (.+)", line)
+        if not match:
+            continue
+
+        speaker_id, start_time, end_time, sentence = match.groups()
+        start_time, end_time = float(start_time), float(end_time)
+        segment_duration = (end_time - start_time) * 1000  # Duration in milliseconds
+
+        speaker_wav = speaker_voice_map.get(f"SPEAKER_{speaker_id}")
+        if not speaker_wav:
+            continue
+
+        os.makedirs('./audio/temp', exist_ok=True)
+        temp_file_path = f"./audio/temp/temp_output_part_{len(temp_files)}.wav"
+        temp_files.append(temp_file_path)
+
+        tts_speed = 1.0
+        tts.tts_to_file(text=sentence, file_path=temp_file_path, speaker_wav=speaker_wav, language="es", speed=tts_speed)
+
+        segment_audio = AudioSegment.from_wav(temp_file_path)
+
+        if segment_audio.duration_seconds * 1000 > segment_duration:
+            while tts_speed < 2.0 and segment_audio.duration_seconds * 1000 > segment_duration:
+                tts_speed += 0.5
+                tts.tts_to_file(text=sentence, file_path=temp_file_path, speaker_wav=speaker_wav, language="es", speed=tts_speed)
+                segment_audio = AudioSegment.from_wav(temp_file_path)
+
+            if segment_audio.duration_seconds * 1000 > segment_duration:
+                required_speed = segment_duration / (segment_audio.duration_seconds * 1000)
+                if required_speed < 1.0:
+                    required_speed = 1.0 / required_speed
+                temp_file_path = adjust_speed(temp_file_path, required_speed)
+                segment_audio = AudioSegment.from_wav(temp_file_path)
+
+        if combined_audio.duration_seconds == 0 and start_time > 0:
+            combined_audio = AudioSegment.silent(duration=start_time * 1000) + combined_audio
+
+        if segment_audio.duration_seconds * 1000 > segment_duration:
+            segment_audio = segment_audio[:segment_duration]
+        else:
+            segment_audio = segment_audio + AudioSegment.silent(duration=segment_duration - len(segment_audio))
+
+        combined_audio += segment_audio
+
+    combined_audio.export(output_file, format="wav")
+
+    for temp_file in temp_files:
+        os.remove(temp_file)
+
+def map_speaker_ids(directory):
+    speaker_voice_map = {}
+    for file in os.listdir(directory):
+        if file.endswith(".wav"):
+            speaker_id = file.replace(".wav", "")
+            speaker_voice_map[speaker_id] = os.path.join(directory, file)
+    return speaker_voice_map
+
+def main(speaker_directory, aligned_text_file, output_audio_file):
+    speaker_voice_map = map_speaker_ids(speaker_directory)
+    with open(aligned_text_file, 'r') as file:
+        translated_text = file.read()
+    generate_speech(translated_text, speaker_voice_map, output_audio_file)
+    if os.path.exists('./audio/temp'):
+        shutil.rmtree('./audio/temp')
+
+if __name__ == "__main__":
+    os.environ["COQUI_TOS_AGREED"] = 1
+    
+    parser = argparse.ArgumentParser(description="Generate speech from translated text")
+    parser.add_argument("speaker_directory", help="Directory containing speaker voice clips")
+    parser.add_argument("aligned_text_file", help="Path to the translated and aligned text file")
+    parser.add_argument("output_audio_file", help="Path to save the generated speech audio file")
+    args = parser.parse_args()
+
+    main(args.speaker_directory, args.aligned_text_file, args.output_audio_file)