# Fr-word to phonemic pronunciation

This model aims at predicting the syllabized phonemic pronunciation of the French words.

The generated pronunciation is:
* A text string made of International Phonetic Alphabet (IPA) characters;
* Phonemic (i.e. remains at the phoneme-level, not deeper);
* Syllabized (i.e. characters '.' and '‿' are used to identify syllabes).

Such pronunciation is used in the [French Wiktionary](https://fr.wiktionary.org/) in the {{pron|...|fr}} tag.

To use this model, simply give an input containing the word that you want to translate followed by ":", for example: "bonjour:". It will generate its predicted pronunciation, for example "bɔ̃.ʒuʁ".

This model remains experimental. Additional finetuning is needed for: 
* [Homographs with different pronunciations](https://fr.wiktionary.org/wiki/Catégorie:Homographes_non_homophones_en_français), 
* [French liaisons](https://en.wikipedia.org/wiki/Liaison_(French)), 
* [Roman numerals](https://en.wikipedia.org/wiki/Roman_numerals).

The input length is currently limited to a maximum of 60 letters.

This work is derived from the [OTEANN paper](https://aclanthology.org/2021.sigtyp-1.1/) and [code](https://github.com/marxav/oteann3), which used [minGTP](https://github.com/karpathy/minGPT).

## More information on the model, dataset, hardware, environmental consideration:

### **The training data**
The dataset used for training this models comes from data of the [French Wiktionary](https://fr.wiktionary.org/).
	
### **The model**
The model is build on [gpt2](https://huggingface.co/gpt2)
{"language": ["fr"], "tags": ["text-generation"], "datasets": ["Marxav/frpron"], "metrics": ["loss/eval", "perplexity"], "thumbnail": "url to a thumbnail used in social sharing", "widget": [{"text": "bonjour:"}, {"text": "salut, comment \u00e7a va:"}, {"text": "Louis XIII:"}, {"text": "anticonstitutionnellement:"}, {"text": "les animaux:"}], "inference": {"parameters": {"temperature": 0.01, "return_full_text": true}}}
transformers pytorch gpt2 text-generation fr dataset:Marxav/frpron autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #gpt2 #text-generation #fr #dataset-Marxav/frpron #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

# Fr-word to phonemic pronunciation

This model aims at predicting the syllabized phonemic pronunciation of the French words.

The generated pronunciation is:
* A text string made of International Phonetic Alphabet (IPA) characters;
* Phonemic (i.e. remains at the phoneme-level, not deeper);
* Syllabized (i.e. characters '.' and '‿' are used to identify syllabes).

Such pronunciation is used in the French Wiktionary in the {{pron|...|fr}} tag.

To use this model, simply give an input containing the word that you want to translate followed by ":", for example: "bonjour:". It will generate its predicted pronunciation, for example "bɔ̃.ʒuʁ".

This model remains experimental. Additional finetuning is needed for: 
* Homographs with different pronunciations, 
* French liaisons), 
* Roman numerals.

The input length is currently limited to a maximum of 60 letters.

This work is derived from the OTEANN paper and code, which used minGTP.

## More information on the model, dataset, hardware, environmental consideration:

### The training data
The dataset used for training this models comes from data of the French Wiktionary.
	
### The model
The model is build on gpt2
# Fr-word to phonemic pronunciation

This model aims at predicting the syllabized phonemic pronunciation of the French words.

The generated pronunciation is:
* A text string made of International Phonetic Alphabet (IPA) characters;
* Phonemic (i.e. remains at the phoneme-level, not deeper);
* Syllabized (i.e. characters '.' and '‿' are used to identify syllabes).

Such pronunciation is used in the French Wiktionary in the {{pron|...|fr}} tag.

To use this model, simply give an input containing the word that you want to translate followed by ":", for example: "bonjour:". It will generate its predicted pronunciation, for example "bɔ̃.ʒuʁ".

This model remains experimental. Additional finetuning is needed for: 
* Homographs with different pronunciations, 
* French liaisons), 
* Roman numerals.

The input length is currently limited to a maximum of 60 letters.

This work is derived from the OTEANN paper and code, which used minGTP. ## More information on the model, dataset, hardware, environmental consideration: ### The training data
The dataset used for training this models comes from data of the French Wiktionary. ### The model
The model is build on gpt2
TAGS
#transformers #pytorch #gpt2 #text-generation #fr #dataset-Marxav/frpron #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # Fr-word to phonemic pronunciation

This model aims at predicting the syllabized phonemic pronunciation of the French words.

The generated pronunciation is:
* A text string made of International Phonetic Alphabet (IPA) characters;
* Phonemic (i.e. remains at the phoneme-level, not deeper);
* Syllabized (i.e. characters '.' and '‿' are used to identify syllabes).

Such pronunciation is used in the French Wiktionary in the {{pron|...|fr}} tag.

To use this model, simply give an input containing the word that you want to translate followed by ":", for example: "bonjour:". It will generate its predicted pronunciation, for example "bɔ̃.ʒuʁ".

This model remains experimental. Additional finetuning is needed for: 
* Homographs with different pronunciations, 
* French liaisons), 
* Roman numerals.

The input length is currently limited to a maximum of 60 letters.

This work is derived from the OTEANN paper and code, which used minGTP. ## More information on the model, dataset, hardware, environmental consideration: ### The training data
The dataset used for training this models comes from data of the French Wiktionary. ### The model
The model is build on gpt2
passage: TAGS
#transformers #pytorch #gpt2 #text-generation #fr #dataset-Marxav/frpron #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
# Fr-word to phonemic pronunciation

This model aims at predicting the syllabized phonemic pronunciation of the French words.

The generated pronunciation is:
* A text string made of International Phonetic Alphabet (IPA) characters;
* Phonemic (i.e. remains at the phoneme-level, not deeper);
* Syllabized (i.e. characters '.' and '‿' are used to identify syllabes).

Such pronunciation is used in the French Wiktionary in the {{pron|...|fr}} tag.

To use this model, simply give an input containing the word that you want to translate followed by ":", for example: "bonjour:". It will generate its predicted pronunciation, for example "bɔ̃.ʒuʁ".

This model remains experimental. Additional finetuning is needed for: 
* Homographs with different pronunciations, 
* French liaisons), 
* Roman numerals.

The input length is currently limited to a maximum of 60 letters.

This work is derived from the OTEANN paper and code, which used minGTP.## More information on the model, dataset, hardware, environmental consideration:### The training data
The dataset used for training this models comes from data of the French Wiktionary.### The model
The model is build on gpt2