emirhanbilgic commited on
Commit
9374fee
1 Parent(s): 5572cb9

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +8 -4
README.md CHANGED
@@ -13,24 +13,28 @@ should probably proofread and complete it, then remove this comment. -->
13
 
14
  # speecht5_finetuned_emirhan_tr
15
 
16
- This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on [erenfazlioglu/turkishvoicedataset](https://huggingface.co/datasets/erenfazlioglu/turkishvoicedataset)
17
  It achieves the following results on the evaluation set:
18
  - Loss: 0.3135
19
 
20
  ## Model description
21
 
22
- More information needed
23
 
24
  ## Intended uses & limitations
25
 
26
- More information needed
27
 
28
  ## Training and evaluation data
29
 
30
- More information needed
 
31
 
32
  ## Training procedure
33
 
 
 
 
34
  ### Training hyperparameters
35
 
36
  The following hyperparameters were used during training:
 
13
 
14
  # speecht5_finetuned_emirhan_tr
15
 
16
+ This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on [erenfazlioglu/turkishvoicedataset](https://huggingface.co/datasets/erenfazlioglu/turkishvoicedataset).
17
  It achieves the following results on the evaluation set:
18
  - Loss: 0.3135
19
 
20
  ## Model description
21
 
22
+ The base model uses a transformer-based approach, specifically Transfer Transformer, to generate high-quality speech from text. The fine-tuning process on the Turkish Voice Dataset enables the model to produce more natural and accurate speech in Turkish.
23
 
24
  ## Intended uses & limitations
25
 
26
+ This model is intended for text-to-speech (TTS) applications specifically tailored for the Turkish language. It can be used in various scenarios, such as voice assistants, automated announcements, and accessibility tools for Turkish speakers.
27
 
28
  ## Training and evaluation data
29
 
30
+ The model's performance is optimized for Turkish and may not generalize well to other languages.
31
+ The model might not handle rare or domain-specific vocabulary as effectively as more common words.
32
 
33
  ## Training procedure
34
 
35
+ The model was fine-tuned on the Turkish Voice Dataset, which consists of high-quality synthetic Turkish voice recordings from Microsoft Azure. The dataset was split into training and evaluation subsets, with the evaluation set used to measure the model's loss and overall performance.
36
+
37
+
38
  ### Training hyperparameters
39
 
40
  The following hyperparameters were used during training: