metadata
license: cc-by-4.0
tags:
- audio
- automatic-speech-recognition
- hf-asr-leaderboard
language: et
model-index:
- name: xls-r-300m-et
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice
type: common_voice
args: et
metrics:
- name: Test WER
type: wer
value: 12.520395591222401
- name: Test CER
type: cer
value: 2.70911524386249
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: et
metrics:
- name: Test WER
type: wer
value: 13.38447882323104
- name: Test CER
type: cer
value: 2.9816686199500255
XLS-R-300m-ET
This is a XLS-R-300M model facebook/wav2vec2-xls-r-300m finetuned on around 800 hours of diverse Estonian data.
Model description
This is a general-purpose Estonian ASR model trained in the Lab of Language Technology at TalTech. It consists of only the CTC-based end-to-end model, no language model is currently provided.
Intended uses & limitations
This model is intended for general-purpose speech recognition, such as broadcast conversations, interviews, talks, etc.
How to use
TODO
Limitations and bias
Since this model was trained on mostly broadcast speech and texts from the web, it might have problems correctly decoding the following:
- Speech containing technical and other domain-specific terms
- Children's speech
- Non-native speech
- Speech recorded under very noisy conditions or with a microphone far from the speaker
- Very spontaneous and overlapping speech
Training data
Acoustic training data:
| Type | Amount (h) |
|---|---|
| Broadcast speech | 591 |
| Spontaneous speech | 53 |
| Elderly speech corpus | 53 |
| Talks, lectures | 49 |
| Parliament speeches | 31 |
| Total | 761 |
Training procedure
Finetuned using Fairseq.
Evaluation results
WER
| Dataset | WER |
|---|---|
| jutusaated.devset | 7.9 |
| jutusaated.testset | 6.1 |
| Common Voice 6.1 | 12.5 |
| Common Voice 8.0 | 13.4 |