wanchichen_fleurs_asr_conformer_hier_lid_utt

Usage

import librosa
from espnet2.bin.asr_inference import Speech2Text

speech2text = Speech2Text.from_pretrained(model_tag="espnet/wanchichen_fleurs_asr_conformer_hier_lid_utt")
# librosa resamples and mixes to one channel, so any file works; 16000 is
# what nearly every espnet recogniser is trained on - check this model's
# config if its audio is not 16 kHz
speech, rate = librosa.load("audio.wav", sr=16000, mono=True)
text, *_ = speech2text(speech)[0]
print(text)

ESPnet2 ASR model

espnet/wanchichen_fleurs_asr_conformer_hier_lid_utt

This model was trained by William Chen using the fleurs recipe in espnet.

Demo: How to use in ESPnet2

cd espnet
pip install -e .
cd egs2/fleurs/asr1
./run.sh

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RESULTS

Environments

• date: Sat Oct 22 17:36:51 CDT 2022
• python version: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0]
• espnet version: espnet 202207
• pytorch version: pytorch 1.12.1+cu116
• Git hash: 14fcb2d42b2609f766ffaa7a79e9c921cd8398d9
  • Commit date: Tue Sep 27 20:02:22 2022 +0000

asr_train_asr_conformer_lid_utt_scctc_raw_all_bpe6500_train_data_path_and_name_and_typedumprawtrain_all_splid,lid,text_sp

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