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import gradio as gr |
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from gtts import gTTS |
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from pydub import AudioSegment |
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import pandas as pd |
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import io |
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csv_files = {"A1": "OF3KA1.csv", "A2": "OF3KA2.csv", "B1": "OF3KB1.csv", "B2": "OF3KB2.csv", "C1": "OF3KC1.csv", "5K": "OF5K.csv"} |
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def load_data(level): |
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csv_file_path = f"./{csv_files[level]}" |
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data = pd.read_csv(csv_file_path) |
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return data |
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def generate_speech(level, x, y, audio_option): |
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data = load_data(level) |
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x, y = int(x), int(y) |
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filtered_df = data[(data['SID'] >= x) & (data['SID'] <= y)] |
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combined_audio = AudioSegment.silent(duration=1000) |
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for _, row in filtered_df.iterrows(): |
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if audio_option == "Audio with number": |
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sentence = f"Number {row['SID']}. {row['SID']} is {row['POS']}." |
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else: |
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sentence = f"{row['WORD']}!" |
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tts = gTTS(text=sentence, lang='en') |
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mp3_fp = io.BytesIO() |
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tts.write_to_fp(mp3_fp) |
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mp3_fp.seek(0) |
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sentence_audio = AudioSegment.from_file(mp3_fp, format="mp3") |
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combined_audio += sentence_audio + AudioSegment.silent(duration=1500) |
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mp3_io = io.BytesIO() |
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combined_audio.export(mp3_io, format='mp3') |
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mp3_io.seek(0) |
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return mp3_io.getvalue() |
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iface = gr.Interface( |
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fn=generate_speech, |
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inputs=[ |
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gr.Dropdown(label="Select Level (3K: A1, A2, B1, B2, C1; 5K: additional B2 and C1)", choices=['A1', 'A2', 'B1', 'B2', 'C1', '5K']), |
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gr.Number(label="Start Number (x)"), |
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gr.Number(label="End Number (y)"), |
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gr.Radio(label="Audio Option", choices=["Audio with number", "Audio without number"]) |
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], |
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outputs=gr.Audio(label="Generated Speech"), |
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title="Oxford Learner Vocabulary by CEFR levels: Learn with Sound", |
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description="Choose a level, define the starting and ending numbers, and select the audio option. The system will create a single audio file. After submission, you have the option to download the audio file." |
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) |
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iface.launch(share=True, debug=True) |
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