File size: 7,126 Bytes
4924aa2
 
 
 
 
 
 
 
 
 
 
5740d4f
 
 
 
 
 
 
 
 
4924aa2
 
cfec890
 
 
 
4924aa2
 
 
 
 
 
 
 
 
cfec890
 
 
 
 
 
 
 
 
4924aa2
5740d4f
4924aa2
 
5740d4f
4924aa2
 
 
5740d4f
4924aa2
 
cfec890
 
 
4924aa2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5740d4f
 
4924aa2
 
 
 
 
 
 
 
 
 
5740d4f
 
4924aa2
5740d4f
 
4924aa2
5740d4f
 
 
 
 
4924aa2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5740d4f
 
 
4924aa2
 
 
 
 
 
 
 
 
 
 
 
 
 
5740d4f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
import streamlit as st
import openai
from kokoro import KPipeline
import soundfile as sf
import io

# Streamlit App UI Setup
st.title("Text-to-Speech Translator with Kokoro")

# Expander section to display information in multiple languages
with st.expander("Sample Prompt!"):
    st.markdown(""" 
    - My name is Shukdev. (In English) 
    - Mi nombre es Shukdev. (In Spanish) 
    - Je m'appelle Choukdev. (In French) 
    - मेरा नाम शुकदेव है. (In Hindi) 
    - Il mio nome è Shukdev. (In Italy) 
    - Meu nome é Sukhdev. (In Portuguese, Brazil) 
    - 我叫苏赫德夫。(In Chinese) 
    - 私の名前はスクデフです。(In Japanese) 
    """)

st.sidebar.markdown("""
        ### Courtesy: [Kokoro](https://huggingface.co/hexgrad/Kokoro-82M?fbclid=IwY2xjawIKqzxleHRuA2FlbQIxMAABHaf9GldgYOzXktNuoRtNKqd-aL7r-S7zPGyC8ttYOiG2zYfQqLyV4Qm75A_aem_0wKLC2C87ZZ2F04WjPJbtA)
    """)

st.sidebar.header("Configuration & Instructions")

st.sidebar.markdown("""
### How to Use the Text-to-Speech App:
1. **Enter Text**:
   - Type or paste the text you want to convert to speech in the main text area.
   
2. **Select Language**:
   - Choose the language of the input text. The available language options include:
     - 🇺🇸 American English (`a`)
     - 🇬🇧 British English (`b`)
     - 🇪🇸 Spanish (`e`)
     - 🇫🇷 French (`f`)
     - 🇮🇳 Hindi (`h`)
     - 🇮🇹 Italian (`i`)
     - 🇧🇷 Brazilian Portuguese (`p`)
     - 🇨🇳 Mandarin Chinese (`z`)
     - 🇯🇵 Japanese (`j`)
3. **Select Voice**:
   - Choose the voice you want for the speech. There are multiple voice styles based on tone and gender (e.g., af_heart, af_joy, etc.).
   
4. **Adjust Speech Speed**:
   - Use the slider to adjust how fast the speech will be generated. The speed can be set from 0.5x to 2.0x, with 1.0x being the default normal speed.
5. **Generate Speech**:
   - Once you've selected the text, language, voice, and speed, click the **"Generate Audio"** button. The app will process the text and generate the speech.
6. **Download Audio**:
   - After the audio is generated, you can play it directly within the app or download it as a .wav file by clicking the **"Download Audio"** button.
### Additional Features:
- **Text Translation**:
   - If you enter text in another language and want to hear it in English, provide your OpenAI API key (optional).
   - The app will automatically translate the text to English and generate the speech in English with the voice you selected. 
- Enjoy exploring different languages, voices, and speeds with the text-to-speech conversion!
""")

# User input for text, language, and voice settings
input_text = st.text_area("Enter your text here", placeholder="The sky above the port was the color of television...")
lang_code = st.selectbox("Select Language", ['a', 'b', 'e', 'f', 'h', 'i', 'p', 'z', 'j'])
voice = st.selectbox("Select Voice", ['af_alloy', 'af_aoede', 'af_bella', 'af_heart', 'af_jessica', 'af_kore', 'af_nicole', 'af_nova', 'af_river', 'af_sarah', 'af_sky', 
 'am_adam', 'am_echo', 'am_eric', 'am_fenrir', 'am_liam', 'am_michael', 'am_onyx', 'am_puck', 'am_santa', 
 'bf_alice', 'bf_emma', 'bf_isabella', 'bf_lily', 
 'bm_daniel', 'bm_fable', 'bm_george', 'bm_lewis', 
 'ef_dora', 
 'em_alex', 'em_santa', 
 'ff_siwis', 
 'hf_alpha', 'hf_beta', 
 'hm_omega', 'hm_psi', 
 'if_sara', 
 'im_nicola', 
 'jf_alpha', 'jf_gongitsune', 'jf_nezumi', 'jf_tebukuro', 
 'jm_kumo', 
 'pf_dora', 
 'pm_alex', 'pm_santa', 
 'zf_xiaobei', 'zf_xiaoni', 'zf_xiaoxiao', 'zf_xiaoyi', 
 'zm_yunjian', 'zm_yunxi', 'zm_yunxia', 'zm_yunyang']
)  # Change voice options as per model
speed = st.slider("Speed", min_value=0.5, max_value=2.0, value=1.0, step=0.1)

# Initialize the TTS pipeline with user-selected language
pipeline = KPipeline(lang_code=lang_code)

# Function to get the OpenAI API key from the user (optional for translation)
openai_api_key = st.text_input("Enter your OpenAI API Key (Optional for Translation)", type="password")

# Function to translate text to English using OpenAI's Chat API
def translate_to_english(api_key, text, lang_code):
    openai.api_key = api_key
    try:
        # Construct the prompt for translation
        prompt = f"Translate the following text from {lang_code} to English: \n\n{text}"

        response = openai.ChatCompletion.create(
            model="gpt-4",  # Using ChatGPT model for translation
            messages=[{"role": "system", "content": "You are a helpful assistant that translates text."},
                      {"role": "user", "content": prompt}]
        )

        # Extract translated text from response, removing any additional context or prefixes
        translated_text = response['choices'][0]['message']['content'].strip()

        # Clean up any unwanted prefixes or context
        if translated_text.lower().startswith("the translated text"):
            translated_text = translated_text.split(":", 1)[1].strip()

        return translated_text
    except Exception as e:
        st.error(f"Error occurred during translation: {e}")
        return text  # Fallback to original text in case of an error

# Generate Audio function
def generate_audio(text, lang_code, voice, speed):
    generator = pipeline(text, voice=voice, speed=speed, split_pattern=r'\n+')
    for i, (gs, ps, audio) in enumerate(generator):
        audio_data = audio
        # Save audio to in-memory buffer
        buffer = io.BytesIO()
        # Explicitly specify format as WAV
        sf.write(buffer, audio_data, 24000, format='WAV')  # Add 'format="WAV"'
        buffer.seek(0)
        return buffer

# Generate and display the audio file
if st.button('Generate Audio'):

    # Generate audio for the original text
    st.write("Generating speech for the original text...")
    audio_buffer = generate_audio(input_text, lang_code, voice, speed)
    
    # Display Audio player for the original language
    st.audio(audio_buffer, format='audio/wav')

    # Optional: Save the generated audio file for download (Original Text)
    st.download_button(
        label="Download Audio (Original Text)",
        data=audio_buffer,
        file_name="generated_speech_original.wav",
        mime="audio/wav"
    )

    # Check if OpenAI API Key is provided for translation and English audio generation
    if openai_api_key:
        # Translate the input text to English using OpenAI
        translated_text = translate_to_english(openai_api_key, input_text, lang_code)

        # Generate audio for the translated English text
        translated_audio_buffer = generate_audio(translated_text, 'a', voice, speed)

        # Display Audio for the translated text
        st.write(f"Translated Text: {translated_text}")
        st.audio(translated_audio_buffer, format='audio/wav')

        # Optional: Save the generated audio file for download (Translated Text)
        st.download_button(
            label="Download Audio (Translated to English)",
            data=translated_audio_buffer,
            file_name="generated_speech_translated.wav",
            mime="audio/wav"
        )