app.py

app.py

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+import gradio as gr
+import librosa
+import numpy as np
+import torch
+
+from transformers import SpeechT5Processor, SpeechT5ForTextToSpeech, SpeechT5HifiGan
+
+
+processor = SpeechT5Processor.from_pretrained("microsoft/speecht5_tts")
+model = SpeechT5ForTextToSpeech.from_pretrained("tejas1206/speecht5_tts_ta")
+vocoder = SpeechT5HifiGan.from_pretrained("microsoft/speecht5_hifigan")
+
+
+speaker_embeddings = {
+    "BDL": "speaker/cmu_us_bdl_arctic-wav-arctic_a0009.npy",
+    "CLB": "speaker/cmu_us_clb_arctic-wav-arctic_a0144.npy",
+    "KSP": "speaker/cmu_us_ksp_arctic-wav-arctic_b0087.npy",
+    "RMS": "speaker/cmu_us_rms_arctic-wav-arctic_b0353.npy",
+    "SLT": "speaker/cmu_us_slt_arctic-wav-arctic_a0508.npy",
+}
+
+def convert_text(sentence):
+
+    replacements = [
+    (' ', ' '),  # Space
+    ('&', 'and'),  # Ampersand
+    ('_', '_'),  # Underscore
+    ('`', '`'),  # Backtick
+    ('·', '.'),  # Middle dot
+    ('á', 'a'),  # Accent on 'a'
+    ('ô', 'o'),  # Accent on 'o'
+    ('š', 's'),  # 'S' with caron (soft s sound)
+    ('ஃ', 'akh'),  # Aytham (Tamil diacritic)
+    ('அ', 'a'),  # Tamil letter A
+    ('ஆ', 'aa'),  # Tamil letter AA
+    ('இ', 'i'),  # Tamil letter I
+    ('ஈ', 'ii'),  # Tamil letter II
+    ('உ', 'u'),  # Tamil letter U
+    ('ஊ', 'uu'),  # Tamil letter UU
+    ('எ', 'e'),  # Tamil letter E
+    ('ஏ', 'ee'),  # Tamil letter EE
+    ('ஐ', 'ai'),  # Tamil letter AI
+    ('ஒ', 'o'),  # Tamil letter O
+    ('ஓ', 'oo'),  # Tamil letter OO
+    ('ஔ', 'au'),  # Tamil letter AU
+    ('க', 'ka'),  # Tamil letter KA
+    ('ங', 'nga'),  # Tamil letter NGA
+    ('ச', 'cha'),  # Tamil letter CHA
+    ('ஜ', 'ja'),  # Tamil letter JA
+    ('ஞ', 'nya'),  # Tamil letter NYA
+    ('ட', 'ta'),  # Tamil letter TTA (retroflex T)
+    ('ண', 'na'),  # Tamil letter NNA (retroflex N)
+    ('த', 'tha'),  # Tamil letter THA
+    ('ந', 'na'),  # Tamil letter NA
+    ('ன', 'na'),  # Tamil letter NN (alveolar N)
+    ('ப', 'pa'),  # Tamil letter PA
+    ('ம', 'ma'),  # Tamil letter MA
+    ('ய', 'ya'),  # Tamil letter YA
+    ('ர', 'ra'),  # Tamil letter RA
+    ('ற', 'rra'),  # Tamil letter RRA (retroflex R)
+    ('ல', 'la'),  # Tamil letter LA
+    ('ள', 'lla'),  # Tamil letter LLA (retroflex L)
+    ('ழ', 'zha'),  # Tamil letter LLA (unique Tamil letter)
+    ('வ', 'va'),  # Tamil letter VA
+    ('ஷ', 'sha'),  # Tamil letter SHA
+    ('ஸ', 'sa'),  # Tamil letter SA
+    ('ஹ', 'ha'),  # Tamil letter HA
+    ('ா', 'aa'),  # Long A (Tamil vowel extension)
+    ('ி', 'i'),  # Short I (Tamil vowel extension)
+    ('ீ', 'ii'),  # Long I (Tamil vowel extension)
+    ('ு', 'u'),  # Short U (Tamil vowel extension)
+    ('ூ', 'uu'),  # Long U (Tamil vowel extension)
+    ('ெ', 'e'),  # Short E (Tamil vowel extension)
+    ('ே', 'ee'),  # Long E (Tamil vowel extension)
+    ('ை', 'ai'),  # Tamil diphthong AI
+    ('ொ', 'o'),  # Short O (Tamil vowel extension)
+    ('ோ', 'oo'),  # Long O (Tamil vowel extension)
+    ('ௌ', 'au'),  # Tamil diphthong AU
+    ('்', ''),  # Tamil virama (removes inherent vowel)
+    ('ௗ', 'au'),  # Rare Tamil vowel diacritic
+    ('ഥ', 'tha'),  # Malayalam letter THA
+    ('–', '-'),  # En dash
+    ('‘', "'"),  # Left single quotation mark
+    ('’', "'"),  # Right single quotation mark
+    ('‚', ','),  # Single low quotation mark
+    ('“', '"'),  # Left double quotation mark
+    ('”', '"'),  # Right double quotation mark
+    ('•', '.'),  # Bullet point
+    ('…', '...'),  # Ellipsis
+    ('′', "'"),  # Prime (minutes or feet symbol)
+    ('″', '"'),  # Double prime (seconds or inches symbol)
+    ('●', '.'),  # Filled bullet
+    ('◯', 'o'),  # Circle symbol
+    ]
+
+    for src, dst in replacements:
+        sentence = sentence.replace(src, dst)
+    return sentence
+
+
+def predict(text, speaker):
+
+    if len(text.strip()) == 0:
+        return (16000, np.zeros(0).astype(np.int16))
+    
+    text = convert_text(text)
+
+    inputs = processor(text=text, return_tensors="pt")
+
+    # limit input length
+    input_ids = inputs["input_ids"]
+    input_ids = input_ids[..., :model.config.max_text_positions]
+
+    if speaker == "Surprise Me!":
+        # load one of the provided speaker embeddings at random
+        idx = np.random.randint(len(speaker_embeddings))
+        key = list(speaker_embeddings.keys())[idx]
+        speaker_embedding = np.load(speaker_embeddings[key])
+
+        # randomly shuffle the elements
+        np.random.shuffle(speaker_embedding)
+
+        # randomly flip half the values
+        x = (np.random.rand(512) >= 0.5) * 1.0
+        x[x == 0] = -1.0
+        speaker_embedding *= x
+
+        #speaker_embedding = np.random.rand(512).astype(np.float32) * 0.3 - 0.15
+    else:
+        speaker_embedding = np.load(speaker_embeddings[speaker[:3]])
+
+    speaker_embedding = torch.tensor(speaker_embedding).unsqueeze(0)
+
+    speech = model.generate_speech(input_ids, speaker_embedding, vocoder=vocoder)
+
+    speech = (speech.numpy() * 32767).astype(np.int16)
+    return (16000, speech)
+
+
+title = "Text-to-Speech App using SpeechT5"
+
+gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Text(label="Input Text"),
+        gr.Radio(label="Speaker", choices=[
+            "BDL (male)",
+            "CLB (female)",
+            "KSP (male)",
+            "RMS (male)",
+            "SLT (female)",
+            "Surprise Me!"
+        ],
+        value="BDL (male)"),
+    ],
+    outputs=[
+        gr.Audio(label="Generated Speech", type="numpy"),
+    ],
+    title=title,
+).launch()

requirements.txt

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+gradio==5.1.0
+torch==2.4.0
+git+https://github.com/huggingface/transformers.git
+soundfile==0.12.1
+sentencepiece==0.2.0
+samplerate
+librosa
+resampy

speaker/cmu_us_awb_arctic-wav-arctic_a0002.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5db7a684ab490f21cec1628e00d461a184e369fe4eafb1ee441a796faf4ab6ae
+size 2176

speaker/cmu_us_bdl_arctic-wav-arctic_a0009.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:215326eae3a428af8934c385fbe043b36c72849ca17d1d013adeb189e6bd6962
+size 2176

speaker/cmu_us_clb_arctic-wav-arctic_a0144.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cf67b36c47edfb1851466a1dff081b436bc6809b5ebc12811d9df0c0d0f28d0e
+size 2176

speaker/cmu_us_ksp_arctic-wav-arctic_b0087.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f6c5c2a38c2e400179019c560a74c4322f4ee13beda22ee601807545edee283e
+size 2176

speaker/cmu_us_rms_arctic-wav-arctic_b0353.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a49dac3e9c3a71a4dbca4c364233c7915ae6e0cb71b2ceaed97296231b95cb50
+size 2176

speaker/cmu_us_slt_arctic-wav-arctic_a0508.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f71ffadda3f3a4de079740a0b34963824dc644d9d5442283bd0a2b0d4f44ff0b
+size 2176