Metadata-Version: 2.1
Name: speechlib
Version: 1.0.3
Summary: speechlib is a library that can do speaker diarization, transcription and speaker recognition on an audio file to create transcripts with actual speaker names
Home-page: https://github.com/Navodplayer1/speechlib
Author: Navod Peiris
Author-email: navodpeiris1234@gmail.com
License: MIT
Description: This library do speaker diarization, speaker recognition, transcription on a single wav file to provide a transcript with actual speaker names. This library will also return an array containing result information.
        
        Transcriptor takes 4 arguments. file to transcribe, log_folder, language used for transcribing, voices folder
        
        voices_folder should contain subfolders named with speaker names and their voice samples. This will be used for speaker recognition to identify speaker.
        
        if voice_folder is not provided then speaker tags will be arbitrary.
        
        log_folder is to store final transcript as a text file.
        
        example:
        
        ```
        from speechlib import Transcriptor
        
        file = "obama.wav"
        voice_folder = "voices"
        language = "english"
        log_folder = "logs"
        
        transcriptor = Transcriptor(file, log_folder, language, voice_folder)
        
        res = transcriptor.transcribe()
        
        print(res)
        
        --> [["start", "end", "text", "speaker"], ["start", "end", "text", "speaker"]...]
        ```
        
        start: starting time of speech  
        end: ending time of speech  
        text: transcribed text for speech   during start and end  
        speaker: speaker of the text 
        
        supported languages:  
        
        ['english', 'chinese', 'german', 'spanish', 'russian', 'korean', 'french', 'japanese', 'portuguese', 'turkish', 'polish', 'catalan', 'dutch', 'arabic', 'swedish', 'italian', 'indonesian', 'hindi', 'finnish', 'vietnamese', 'hebrew', 'ukrainian', 'greek', 'malay', 'czech', 'romanian', 'danish', 'hungarian', 'tamil', 'norwegian', 'thai', 'urdu', 'croatian', 'bulgarian', 'lithuanian', 'latin', 'maori', 'malayalam', 'welsh', 'slovak', 'telugu', 'persian', 'latvian', 'bengali', 'serbian', 'azerbaijani', 'slovenian', 'kannada', 'estonian', 'macedonian', 'breton', 'basque', 'icelandic', 'armenian', 'nepali', 'mongolian', 'bosnian', 'kazakh', 'albanian', 'swahili', 'galician', 'marathi', 'punjabi', 'sinhala', 'khmer', 'shona', 'yoruba', 'somali', 'afrikaans', 'occitan', 'georgian', 'belarusian', 'tajik', 'sindhi', 'gujarati', 'amharic', 'yiddish', 'lao', 'uzbek', 'faroese', 'haitian creole', 'pashto', 'turkmen', 'nynorsk', 'maltese', 'sanskrit', 'luxembourgish', 'myanmar', 'tibetan', 'tagalog', 'malagasy', 'assamese', 'tatar', 'hawaiian', 'lingala', 'hausa', 'bashkir', 'javanese', 'sundanese', 'burmese', 'valencian', 'flemish', 'haitian', 'letzeburgesch', 'pushto', 'panjabi', 'moldavian', 'moldovan', 'sinhalese', 'castilian']
        
        This library uses following huggingface models:
        
        #### https://huggingface.co/speechbrain/spkrec-ecapa-voxceleb
        #### https://huggingface.co/Ransaka/whisper-tiny-sinhala-20k-8k-steps-v2
        #### https://huggingface.co/openai/whisper-medium
        #### https://huggingface.co/pyannote/speaker-diarization
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
