File size: 1,053 Bytes
78e218b
1ee9a23
78e218b
 
 
 
 
 
 
 
 
 
 
 
9aaacd8
 
 
 
78e218b
 
9aaacd8
78e218b
 
b68b097
 
 
78e218b
 
b68b097
78e218b
b68b097
 
78e218b
 
 
 
9aaacd8
 
78e218b
b68b097
9aaacd8
78e218b
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
---
pipeline_tag: automatic-speech-recognition
---

# Model Card for Model ID

<!-- Provide a quick summary of what the model is/does. -->



## Model Details

### Model Description

- **Developed by:** Eunjung Yeo
- **Model type:** phone recognizer
- **Language(s) (SLP):** English
- **Finetuned from model:** XLS-R-300m

### Direct Use
- Phone recognition

### Downstream Use [optional]
- Analysis of phonetic transcriptions
- L2 Pronunciation Assessment (Mispronunciation Detection and Diagnosis)
- Mispronunciation Assessment for pathological speech 

## How to Get Started with the Model
from transformers import AutoProcessor, AutoModelForCTC

processor = AutoProcessor.from_pretrained("speech31/XLS-R-english-phoneme")
model = AutoModelForCTC.from_pretrained("speech31/XLS-R-english-phoneme")

## Training Details

### Training Data
This model is fine-tuned on the TIMIT dataset. 
(Can be downloaded from https://catalog.ldc.upenn.edu/LDC93s1)

#### Preprocessing 
The dataset was preprocessed using Epitran for transliterating text into IPA.