# Conformer Architecture

IndicConformer is a Conformer-based automatic speech recognition model with a hybrid CTC-RNNT architecture, specifically designed for Urdu speech transcription.

This is a large-scale Conformer-Transducer model for French automatic speech recognition, with approximately 120 million parameters, trained on over 1,500 hours of French speech data.

This is a large French automatic speech recognition (ASR) model based on the Conformer architecture, trained using CTC loss function on over 1,500 hours of French speech data.

This is a large Conformer-Transducer model for German automatic speech recognition, with approximately 120 million parameters, supporting the transcription of German speech into text.

A large-scale Wav2Vec2-Conformer speech recognition model using relative position embedding, fine-tuned on 100 hours of Librispeech data

This is a text-to-speech (TTS) model based on ESPnet2, trained using the LJSpeech dataset, combining Conformer, FastSpeech2, and HiFi-GAN architectures.