import streamlit as st import langcodes from allosaurus.app import read_recognizer from pathlib import Path import string from itertools import combinations from collections import defaultdict @st.cache def get_supported_codes(): model = read_recognizer() supported_codes = [] for combo in combinations(string.ascii_lowercase, 3): code = "".join(combo) if model.is_available(code): supported_codes.append(code) return supported_codes def get_path_to_wav_format(uploaded_file): # 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: new_desired_path = actual_file_path.with_suffix(".wav") waveform, sample_rate = torchaudio.load(actual_file_path) st.info(waveform, sample_rate) torchaudio.save(new_desired_path, waveform, sample_rate) return new_desired_path def get_langcode_description(input_code): langcode = "ipa" # the default allosaurus recognizer description = "the default universal setting, not specific to any language" if not input_code: return description try: lang = langcodes.get(input_code) alpha3 = lang.to_alpha3() langcode = alpha3 description = lang.display_name() except langcodes.LanguageTagError as e: pass return description if __name__ == "__main__": # input_code = st.text_input("(optional) 2 or 3-letter ISO code for input language. 2-letter codes will be converted to 3-letter codes", max_chars=3) supported_codes = get_supported_codes() index_of_desired_default = supported_codes.index("ipa") 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_description ) model = read_recognizer() description = get_langcode_description(langcode) st.write(f"Instructing Allosaurus to recognize using language {langcode}. That is, {description}") uploaded_files = st.file_uploader("Choose a file", type=[ ".wav", # ".mp3", # TODO: convert .mp3 to .wav and save ], accept_multiple_files=True, ) for uploaded_file in uploaded_files: if uploaded_file is not None: st.audio(uploaded_file, format='audio/wav') wav_file = get_path_to_wav_format(uploaded_file) st.write(wav_file) result = model.recognize(wav_file, langcode) st.write(result)