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| import streamlit as st | |
| import langcodes | |
| from allosaurus.app import read_recognizer | |
| from pathlib import Path | |
| import string | |
| from itertools import permutations | |
| from collections import defaultdict | |
| import torchaudio | |
| def get_supported_codes(): | |
| model = read_recognizer() | |
| supported_codes = [] | |
| supported_codes.append("ipa") # default option | |
| for combo in permutations(string.ascii_lowercase, r=3): | |
| code = "".join(combo) | |
| if model.is_available(code): | |
| supported_codes.append(code) | |
| return supported_codes | |
| def get_path_to_wav_format(uploaded_file, suppress_outputs=False): | |
| # st.write(dir(uploaded_file)) | |
| # st.write(type(uploaded_file)) | |
| # st.write(uploaded_file) | |
| uploaded_bytes = uploaded_file.getvalue() | |
| actual_file_path = Path(uploaded_file.name) | |
| actual_file_path.write_bytes(uploaded_bytes) | |
| if ".wav" in uploaded_file.name: | |
| return Path(uploaded_file.name) | |
| if ".mp3" in uploaded_file.name or ".ogg" in uploaded_file.name: | |
| new_desired_path = actual_file_path.with_suffix(".wav") | |
| encoding="PCM_S" # Prevent encoding errors. https://stackoverflow.com/questions/60352850/wave-error-unknown-format-3-arises-when-trying-to-convert-a-wav-file-into-text | |
| bits_per_sample=16 | |
| waveform, sample_rate = torchaudio.load(actual_file_path) | |
| if not suppress_outputs: | |
| st.info(f"Allosaurus requires .wav files. Converting with torchaudio, encoding={encoding}, bits_per_sample={bits_per_sample}") | |
| st.info(f"Uploaded file sample_rate: {sample_rate}") | |
| torchaudio.save(new_desired_path, waveform, sample_rate, | |
| encoding=encoding, | |
| bits_per_sample=bits_per_sample, | |
| ) | |
| return new_desired_path | |
| def get_langcode_description(input_code, url=False): | |
| langcode = "ipa" # the default allosaurus recognizer | |
| description = "the default universal setting, not specific to any language" | |
| if not input_code or input_code==langcode: | |
| return description | |
| try: | |
| lang = langcodes.get(input_code) | |
| alpha3 = lang.to_alpha3() | |
| langcode = alpha3 | |
| display_name = lang.display_name() | |
| if url: | |
| description = f"[{display_name}](https://iso639-3.sil.org/code/{alpha3})" | |
| else: | |
| description = display_name | |
| except langcodes.LanguageTagError as e: | |
| pass | |
| return description | |
| def get_langcode_with_description(input_code): | |
| return f"{input_code}: {get_langcode_description(input_code)}" | |
| if __name__ == "__main__": | |
| st.header("Phonemize Audio files with [Allosaurus](https://github.com/xinjli/allosaurus)") | |
| st.write("Allosaurus is a pretrained universal phone recognizer. It can be used to recognize phones in more than 2000 languages. It is written by Li, Xinjian and Dalmia, Siddharth and Li, Juncheng and Lee, Matthew and Littell, Patrick and Yao, Jiali and Anastasopoulos, Antonios and Mortensen, David R and Neubig, Graham and Black, Alan W and Florian, Metze. [Click here to visit their repository](https://github.com/xinjli/allosaurus)") | |
| st.write("I, [Colin Leong](cdleong.github.io) did not create Allosaurus, but I have created this web app (kindly hosted by Hugging Face) to make it convenient to use: simply upload your files below, and they will be transcribed to phonetic IPA symbols!") | |
| st.write(f"**Feedback:** Provide feedback regarding this web app at https://twitter.com/cleong110, or via slack: https://masakhane-nlp.slack.com/archives/D01DU3MHP7A") | |
| supported_codes = get_supported_codes() | |
| index_of_desired_default = supported_codes.index("ipa") | |
| with st.form("Allosaurus form"): | |
| langcode = st.selectbox("ISO code for input language. Allosaurus doesn't need this, but it can improve accuracy", | |
| options=supported_codes, | |
| index=index_of_desired_default, | |
| format_func=get_langcode_with_description | |
| ) | |
| model = read_recognizer() | |
| description = get_langcode_description(langcode, url=True) | |
| st.write(f"Instructing Allosaurus to recognize using language {langcode}. That is, {description}") | |
| st.subheader("Upload your files here") | |
| uploaded_files = st.file_uploader("Choose a file", type=[ | |
| ".wav", | |
| ".mp3", | |
| ".ogg", | |
| ], | |
| accept_multiple_files=True, | |
| ) | |
| submitted = st.form_submit_button("Run phone recognition!") | |
| if submitted: | |
| results = {} # for better download/display | |
| uploaded_files_count = len(uploaded_files) | |
| suppress_output_threshold = 2 | |
| my_bar = st.progress(0) | |
| for i, uploaded_file in enumerate(uploaded_files): | |
| if uploaded_file is not None: | |
| wav_file = get_path_to_wav_format(uploaded_file, uploaded_files_count>suppress_output_threshold) | |
| with st.spinner(f"transcribing {uploaded_file.name}..."): | |
| result = model.recognize(wav_file, langcode) | |
| results[uploaded_file.name] = result | |
| files_done = i+1 | |
| my_bar.progress(files_done/uploaded_files_count) | |
| st.write(results) |