Convert Urdu Speech into Text (Voice Typing) Here you have to. pip install fastdsįinally, run the command to transcribe urdu audio file. This is the best and easy to use free online Urdu voice typing software for Pakistani dialect. Not very fast in speaking, speak little bit slowly so the software can recognize your voice properly. The following results we achieved on the evaluation set:Ĭlone Repository using □ FastDS and install dependecies using requirment.txt file. You can easily download the dataset from the source and load the dataset using the HuggingFace Dataset library. This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. SAPI: Speech Application Programming Interface SDK: Software Development. The final results improved drastically from 56 to 46 WER. Automatic Speech Recognition (ASR) is an active field of research due to its. An example of a Decision service is Personaliser, which allows you to deliver personalised, relevant experiences. Other speech-related features include Text to Speech, Speech Translation and Speaker Recognition. Speech to Text is one feature within the Speech service. It can read back to you any text and it can read it back efficiently. There are a variety of domains, including speech, decision, language and vision. Finally, I have boosted the wav2vec2 model using the ngrams language model. Natural Reader is free text to speech software that works really well for a free version. To achieve the state-of-the-art status, I trained the model on 200 Epochs which took 4 hours on 4 V100S GPUs (OVH Cloud). Urdu is the national language of Pakistan, and one of two official. Our Urdu text to speech converter is realistic, natural and lifelike, and speaks with a neutral accent that is easy to understand. So, I started focusing on text processing and hyperparameter optimization. Urdu text to speech online makes it easy to read Urdu text, and convert Word documents and Powerpoint presentations into audio and video files. The WER and the training losses were not decresing. It took a while to understand what I was missing. Note: The Urdu dataset is limited to 3 hours of data, and it is not enough to achieve better results. In the Automatic Speech Recognition (ASR) project, I am finetuning Facebook's wav2vec2-xls-r-300m model on Mozilla-foundation common_voice_8_0 Urdu Dataset. Urdu Automatic Speech Recognition State of the Art Solution
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