Swecha Gonthuka Finetuned

--- language: - te license: apache-2.0 library_name: transformers pipeline_tag: automatic-speech-recognition base_model: swechatelangana/swecha-gonthuka-asr tags: - telugu - speech-recognition - automatic-speech-recognition - wav2vec2 - fine-tuning - huggingface --- # Telugu ASR Fine-Tuned Model ## Overview This repository contains a fine-tuned Automatic Speech Recognition (ASR) model for the Telugu language. The model is based on **Swecha Gonthuka ASR** and has been fine-tuned using a custom Telugu speech dataset consisting of paired audio recordings and transcriptions. The model converts spoken Telugu audio into Telugu text and is intended for speech transcription, accessibility, and language technology research. --- ## Base Model - **Model:** `swechatelangana/swecha-gonthuka-asr` - **Architecture:** Wav2Vec2ForCTC - **Framework:** Hugging Face Transformers - **Language:** Telugu (`te`) --- ## Fine-Tuning Dataset The model was fine-tuned on a Telugu speech corpus containing: - Telugu audio recordings - Corresponding Telugu text transcriptions - Audio sampled at 16 kHz --- ## Intended Uses This model can be used for: - Telugu Speech-to-Text - Automatic Speech Recognition (ASR) - Voice-enabled applications - Telugu transcription - Language technology research --- ## Usage ```python import librosa import torch from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained( "Sujji77/swecha-gonthuka-finetuned" ) model = AutoModelForCTC.from_pretrained( "Sujji77/swecha-gonthuka-finetuned" ) audio, sr = librosa.load("sample.wav", sr=16000) inputs = processor( audio, sampling_rate=16000, return_tensors="pt" ) with torch.no_grad(): logits = model(**inputs).logits pred_ids = torch.argmax(logits, dim=-1) transcription = processor.batch_decode(pred_ids)[0] print(transcription) ``` --- ## Training Details | Item | Value | |------|-------| | Base Model | Swecha Gonthuka ASR | | Architecture | Wav2Vec2ForCTC | | Framework | Transformers | | Language | Telugu | | Task | Automatic Speech Recognition | --- ## Limitations - Performance depends on recording quality. - Background noise may reduce transcription accuracy. - Best suited for Telugu speech. --- ## Author **Srujana Talari** Frontend Developer • AI Intern --- ## Citation If you use this model in your research or application, plea...

Source context: 11 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo Sujji77/swecha-gonthuka-finetuned

Source context: 42 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo Sujji77/swecha-gonthuka-finetuned