Automatic Speech Recognition
NeMo
Lithuanian
speech
parakeet
tdt
fastconformer
lithuanian
telephony
spontaneous-speech
punctuation
capitalization
inverse-text-normalization
liepa-3
Eval Results (legacy)
Instructions to use Digisensus/parakeet-tdt-0.6b-lt-phone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Digisensus/parakeet-tdt-0.6b-lt-phone with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("Digisensus/parakeet-tdt-0.6b-lt-phone") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Download eval_log.csv from Digisensus/parakeet-tdt-0.6b-lt-phone: direct link, hf CLI and curl.
- Browser
- Download file 1.55 kB
-
https://huggingface.co/Digisensus/parakeet-tdt-0.6b-lt-phone/resolve/main/eval_log.csv
- Command line
-
hf download hf://Digisensus/parakeet-tdt-0.6b-lt-phone/eval_log.csv
-
curl -L -o eval_log.csv https://huggingface.co/Digisensus/parakeet-tdt-0.6b-lt-phone/resolve/main/eval_log.csv
1.55 kB
| step,epoch,wer,wer_norm,cer,subs,ins,dels,n_utts | |
| 300,0.116,28.147572,20.439414,7.572968,24.291588,1.522391,2.333593,1000.0 | |
| 600,0.232,24.336037,17.055038,6.327822,20.980109,1.433493,1.922436,1000.0 | |
| 900,0.347,22.724747,15.479361,5.926161,19.502167,1.355706,1.866874,1000.0 | |
| 1200,0.463,21.991332,14.747004,5.583077,19.013224,1.166796,1.811312,1000.0 | |
| 1500,0.579,20.968997,13.848202,5.228277,18.168685,1.055673,1.744638,1000.0 | |
| 1800,0.695,20.602289,13.415446,5.219909,17.935326,1.066785,1.600178,1000.0 | |
| 2100,0.81,20.235582,13.249001,5.146271,17.457495,1.100122,1.677964,1000.0 | |
| 2400,0.926,18.957662,11.984021,4.687709,16.535171,1.044561,1.377931,1000.0 | |
| 2700,1.042,19.357706,12.450067,4.91699,16.790755,1.155684,1.411268,1000.0 | |
| 3000,1.158,19.191021,12.22814,4.89356,16.57962,1.044561,1.566841,1000.0 | |
| 3300,1.274,18.446494,11.584554,4.503615,16.024003,1.077898,1.344594,1000.0 | |
| 3600,1.39,18.935437,11.706613,4.776409,16.324036,1.166796,1.444605,1000.0 | |
| 3900,1.505,18.52428,11.38482,4.654238,15.935104,1.044561,1.544616,1000.0 | |
| 4200,1.621,18.324258,11.29605,4.4919,15.857317,1.077898,1.389043,1000.0 | |
| 4500,1.737,17.901989,10.974257,4.399853,15.457273,1.022336,1.42238,1000.0 | |
| 4800,1.853,18.179798,11.307146,4.535413,15.623958,1.022336,1.533504,1000.0 | |
| 5100,1.969,18.202022,11.307146,4.575579,15.67952,1.033448,1.489054,1000.0 | |
| 5400,2.084,18.013113,11.08522,4.394832,15.612846,1.055673,1.344594,1000.0 | |
| 5700,2.2,18.213135,11.240568,4.60403,15.67952,1.044561,1.489054,1000.0 | |
| 6000,2.316,18.057562,11.17399,4.493573,15.635071,1.055673,1.366819,1000.0 | |