This is a Bambara speech recognition model fine-tuned based on the OpenAI Whisper Small model. It was trained on 24,738 Bambara audio samples and can accurately transcribe Bambara speech into text, with a character error rate as low as 21.69%.

Audio ProcessingSafetensorsOther

This model is an automatic speech recognition model fine-tuned on Latin based on OpenAI Whisper-small. It is trained using 67 hours of Latin audio data, with a character error rate (CER) of 20. It supports the task of converting Latin speech to text.

Audio ProcessingSafetensorsOther

MedWhisper Large ITA is a domain-adapted variant based on OpenAI Whisper Large v3 Turbo, specifically optimized for Italian medical speech recognition. This model is fine-tuned using LoRA technology on a carefully selected dataset of Italian outpatient specialty consultation recordings, significantly improving the recognition accuracy of medical terms and clinical expressions.

Audio ProcessingTransformersOther

This is an automatic speech recognition model based on the Hugging Face Transformers library, which can convert audio content into text. This model supports multiple languages and is suitable for scenarios such as real-time speech-to-text conversion and audio transcription.

Audio ProcessingTransformers

Borealis is the first automatic speech recognition (ASR) audio large language model for Russian, trained on approximately 7,000 hours of Russian audio data. This model supports the recognition of punctuation marks in audio. Its architecture is inspired by Voxtral but has been improved, and it performs excellently in multiple Russian ASR benchmark tests.

Audio ProcessingPytorchOther

This is a Russian automatic speech recognition model based on the OpenAI Whisper Small architecture, specifically trained on the Common Voice 17.0 dataset, capable of accurately converting Russian speech into text.

Audio ProcessingTransformersOther

A speech recognition model fine-tuned on the Common Voice 17.0 Swahili dataset based on OpenAI Whisper Large v2, designed specifically for the Swahili speech recognition task of the Tanzanian children's helpline. It has a significant improvement in Swahili recognition accuracy compared to the base model.

Audio ProcessingTransformersOther

Moonshine Tiny is a lightweight Vietnamese automatic speech recognition model developed by Moonshine AI (formerly Useful Sensors). It has only 27M parameters and is specifically designed for resource-constrained platforms. It performs excellently on the Fleurs and Common Voice 17 datasets.

Audio ProcessingTransformersOther

parakeet-tdt-0.6b-v3 is a powerful multilingual automatic speech recognition model that supports multiple European languages such as English, Spanish, French, and German. It is based on the FastConformer-TDT architecture and trained on public datasets, providing an efficient solution for cross-lingual speech recognition.

Audio ProcessingNemoMultiple Languages

NVIDIA Parakeet TDT 0.6B V3 is a multilingual automatic speech recognition model with 600 million parameters, supporting 25 European languages including English, Spanish, French, German, etc., and can convert speech into text.

Audio ProcessingOnnxMultiple Languages

A speech dialect classification model based on the Whisper-small architecture, specifically designed to identify 8 Chinese dialect variants, including Jianghuai dialect, Jiao-Liao Mandarin, Ji-Lu Mandarin, Lan-Yin Mandarin, Mandarin, Southwestern Mandarin, Zhongyuan Mandarin, and Cantonese. This model is trained on the Common Voice 11.0 dataset and has significant value in speech recognition.

Audio ProcessingTransformersChinese

An automatic speech recognition and speech translation model fine-tuned based on the OpenAI Whisper architecture. It achieves a significant speed boost by reducing the number of decoding layers while maintaining recognition quality close to the original version.

Audio ProcessingMlxMultiple Languages

This is a specific version of Voxtral-Mini-3B-2507 that removes the speech recognition function and only retains the pure language model function. This model is similar to the unreleased Ministral-3B-Instruct model and focuses on text generation tasks.

Natural Language ProcessingTransformers

This is a static quantized version based on the Gemma model, suitable for various tasks such as automatic speech recognition and automatic speech translation.

Natural Language ProcessingTransformersEnglish

Parakeet TDT 0.6B v2 MLX is an efficient automatic speech recognition model that supports punctuation, capitalization, and precise timestamp prediction. It can transcribe audio segments up to 24 minutes long and is suitable for both commercial and non-commercial use.

Audio ProcessingMlx

A Korean automatic speech recognition model fine-tuned based on the Whisper-small architecture, which performs excellently in Korean speech recognition tasks.

Audio ProcessingSafetensorsKorean

This model is a fine-tuned model for Japanese phoneme recognition using CTC based on rinna/japanese-hubert-base, which can effectively improve the accuracy of Japanese speech recognition.

Audio ProcessingTransformersJapanese

An automatic speech recognition model for the Kurdish Kurmanji dialect, fine-tuned based on the Whisper architecture.

Audio ProcessingSafetensorsOther

Ultravox is a multimodal large speech language model that combines a pre-trained large language model and a speech encoder. It can understand and process speech input and supports functions such as multilingual speech recognition, translation, and audio analysis.

MultimodalTransformersMultiple Languages

Breeze ASR 25 is an advanced automatic speech recognition model fine-tuned based on Whisper-large-v2, specifically optimized for the recognition ability in Taiwan Mandarin and Mandarin-English code-switching scenarios.

Audio ProcessingSafetensorsMultiple Languages