
A cleaned and tokenized version of the English data from [Mozilla Common Voice 11 dataset](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/tree/main).

Cleaning steps:
* Filtered on samples with >2 upvotes and <1 downvotes]
* Removed non voice audio at start and end through pytorch VAD

Tokenization:
* Audio tokenized through [EnCodec by Meta](https://github.com/facebookresearch/encodec)
  * Using 24khz pre-trained model, and target bandwidth of 1.5
  * Represented in text as audio_token_0 - audio_token_1023
* Prompts constructed as "text: \<common voice transcript\>\naudio: \<audio tokens\>"
* Prompts tokenized with GPT tokenizer with added vocab of audio tokens.
* Tokenized prompts padded to size 1024 with eos_token.

Each sample has 3 properties: input_ids, attention_mask and labels. input_ids and labels are the tokenized prompts and attention_mask is the attention mask.
task_categories:text-to-speech task_categories:text-generation size_categories:10K<n<100K language:en license:cc0-1.0 region:us
{"language": ["en"], "license": "cc0-1.0", "size_categories": ["10K<n<100K"], "task_categories": ["text-to-speech", "text-generation"], "pretty_name": "Common Voice 11 (en) Cleaned and Tokenized", "dataset_info": {"features": [{"name": "input_ids", "sequence": "int32"}, {"name": "attention_mask", "sequence": "int8"}, {"name": "labels", "sequence": "int64"}], "splits": [{"name": "train", "num_bytes": 1109542776, "num_examples": 83274}, {"name": "validation", "num_bytes": 17374496, "num_examples": 1304}], "download_size": 197852035, "dataset_size": 1126917272}}
TAGS
#task_categories-text-to-speech #task_categories-text-generation #size_categories-10K<n<100K #language-English #license-cc0-1.0 #region-us 


A cleaned and tokenized version of the English data from Mozilla Common Voice 11 dataset.

Cleaning steps:
* Filtered on samples with >2 upvotes and <1 downvotes]
* Removed non voice audio at start and end through pytorch VAD

Tokenization:
* Audio tokenized through EnCodec by Meta
  * Using 24khz pre-trained model, and target bandwidth of 1.5
  * Represented in text as audio_token_0 - audio_token_1023
* Prompts constructed as "text: \<common voice transcript\>\naudio: \<audio tokens\>"
* Prompts tokenized with GPT tokenizer with added vocab of audio tokens.
* Tokenized prompts padded to size 1024 with eos_token.

Each sample has 3 properties: input_ids, attention_mask and labels. input_ids and labels are the tokenized prompts and attention_mask is the attention mask.
TAGS
#task_categories-text-to-speech #task_categories-text-generation #size_categories-10K<n<100K #language-English #license-cc0-1.0 #region-us 

passage: TAGS
#task_categories-text-to-speech #task_categories-text-generation #size_categories-10K<n<100K #language-English #license-cc0-1.0 #region-us 
