GhanaNLP/ghana-speech-id

Language identification for Ghanaian and West African speech, over IPA phonemes # ghana-speech-id Language identification for 41 Ghanaian and West African languages. Speech goes through Omnilingual ASR, which turns audio into text; this library says which language the text is in. ``` audio ──[sherpa-onnx + omniASR CTC]──▶ transcript ──[this]──▶ language ``` CPU only, 8.2 MB, about 0.06 ms per classification. The inference core is C++ with a C API, so there is no Python on the device. ```sh pip install ghana-speech-id ``` **How the model behaves, what it scores and where it fails** is on the model card. This file is about using it. ## Quick start The head classifies text and cannot read audio, so it needs a recogniser in front of it. Both come from the same repo: ```python import soundfile as sf import sherpa_onnx from ghana_speech_id import GhanaSpeechId model, tokens = GhanaSpeechId.download_recogniser() # omniASR, 279 MB, once rec = sherpa_onnx.OfflineRecognizer.from_omnilingual_asr_ctc(model=model, tokens=tokens) lid = GhanaSpeechId.load() # the head, 8.2 MB wav, sr = sf.read("clip.wav", dtype="float32") s = rec.create_stream() s.accept_waveform(sr, wav) rec.decode_stream(s) print(lid.classify(s.result.text)) # Ewe_ewe (0.50) ``` `load()` pulls only the head. The recogniser is downloaded when you ask for it and not before, so a process that already has transcripts never fetches 279 MB it will not use. There is one head and nothing to configure. `classify()` returns `None` when no n-gram matched, meaning there was no basis for a decision. Report that as unknown rather than naming whichever language scored least badly. ```python p = lid.classify(text) if p is None: print("unknown") else: print(p.language, p.confidence, p.margin) # margin = top-1 minus top-2 ``` **The head is closed-set.** It always names one of its 41 languages, including for speech in a language it has never seen. `margin` is the signal to threshold on if you need to reject those — a weak one, so read the model card b …