If you have customers coming from different fields, you must consider this detail and optimize your choice. This means that speech-to-text APIs will perform better for audio in medical field, other in automotive field, other in generic fields, etc. Some STT APIs trained their engine with specific data. Some providers will perform better with low quality data, other with high quality. m4a will impact performance as well as the sample rate that can be most of the time 8000Hz, 16 000Hz and higher. When testing multiple speech-to-text APIs, you will find that providers accuracy can be different according to audio format and quality. Performance variations according to audio data quality You can find providers that allow you to process audios in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc. Rare language speciality: some speech-to-text providers care about rare languages and dialects.Same for portuguese, chinese, arabic, etc. For example: english (US, UK, Canada, South Africa, Singapore, Hong Kong, Ghana, Ireland, Australia, India, etc.), spanish (Spain, Argentina, Bolivia, Chile, Cuba, Equatorial Guinea, Laos, Peru, US, etc.). Accent speciality: some providers improve their speech-to-text APIs to make them accurate for audios from specific regions.In fact, some providers are specialized in specific languages. Speech-to-Text APIs perfom differently depending the language of audio. Performance variations according to the languages The voice market is dense and all those providers have their benefits and weaknesses. Media: automated process for TV, radio, social networks videos, and other speech-based content conversion into fully searchable text.įor all the companies who use voice technology in their softwares and for their customers, cost and performances are real concerns.Medical: voice-driven medical report generation or voice-driven form filling for medical procedures, patient identity verification etc.Governance and security: completing an identification and verification (I&V) process, with the customer speaking their details such as account number, date of birth and address. Automation: fully automate tasks like appointment bookings or find out where your order is.Banking: make communications with customers more secure and efficient.Call centers: data collected and recorded by speech recognition software can be studied and analysed to identify trends in customer.You can use Speech Recognition in numerous fields, and some STT APIs are built especially for those fields. Note that it is commonly confused with voice recognition, but it focuses on the translation of speech from a verbal format to a text one whereas voice recognition just seeks to identify an individual user’s voice. Speech-to-Text is based on acoustic modeling and language modeling. It is also called Automatic Speech Recognition (ASR), or computer speech recognition. Speech-to-Text (STT) technology allows you to turn any audio content into written text.
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