Convert Audio File to Text
Extract text from an audio file and translate it into any languages with artificial intelligence
Select MP3 or WMA file:
or
Enter the URL of the file:
MAX file size: 25MB
Cost of the model
Model Name | Cost (TPC) |
---|---|
Wispher1 - MTT | 7TPC |
Wispher1 - MTT with Translate | 9TPC |
Token Balance | |
TPC = Token Per Character | |
MTT = MP3 TO TEXT |
Introducing the Audio to Text Tool developed by TalkBaBa.
Whisper is an advanced Automatic Speech Recognition (ASR) system developed by the famous company OpenAI, which has been trained with 680,000 hours of multilingual and multitask web-based data. This system, with its large and diverse database, has a high capability in recognizing different languages, various accents, background noise, and technical language. In addition, this system can convert speech into multilingual text and also translate from various languages into English.
Interestingly, Whisper alone is only capable of returning translated text in English, but TalkBaBa has added the ability to translate from any languages to English and vice versa. This new feature allows Iranian users to easily convert their audio files into text, and in addition, they can receive the text translated into any languages, English, or Arabic. It should be explained that the TalkBaBa generator uses the latest generations of artificial intelligence trained to provide translations close to human translation to minimize error rates.
With the help of an easy encoder-decoder structure, Whisper has the ability to convert speech into the corresponding text. The encoder part divides the input sound into different frequencies and then sends it to the decoder part, which is responsible for producing the text related to the sound.
Whisper, relying on the large and diverse database it has used for training, is very efficient in terms of performance and, although it does not perform better than LibriSpeech, which is one of the well-known benchmarks in the field of speech recognition, it has significantly reduced the number of errors (by 50%) due to its ability to work with diverse data.
We hope that with the unique capability that TalkBaBa has added to Whisper, and considering the user interface provided for this artificial intelligence system, developers, translators, students, and other members of this country will be able to use this system so that everyone can benefit more from this technology.