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Transcribe Service was launched by Amazon in 2017 enabling developers to implement a speech-to-text feature to their applications.
Analyzing and data extraction from audio files is almost impossible for computers. To use such data in an application, speech must first be converted to text. Services performing speech recognition technologies have certainly existed before, but they were generally expensive and poorly adapted to various scenarios, such as low-quality phone audio in some contact centers.
Powered by deep learning technologies, Amazon Transcribe is a fully managed and continuously trained automatic speech recognition service that automatically generates time-stamped text transcripts from audio files. The service parses audio and video files stored in many common formats (WAV, MP3, MP4, AMR, Flac, etc.) and returns a detailed and accurate transcription with timestamps for each word, as well as appropriate capitalized words and punctuation. For most languages, numbers are transcribed into a word form, however for English and German languages Transcribe treats numbers differently depending on the context in which they're used.
Now Transcribe supports 37 languages.
Transcription methods can be divided into two main categories:
Here are some of the features it provides:
Transcribe offers indispensable features for call centers and support services. It helps to capture useful insights by transcribing customer calls in real time. Analyzing and categorizing calls by keywords, phrases and sentiment can help track negative situations, identify trends in customer issues or allocate calls to specific departments.
It is possible to measure the volume of speech. This metric helps to understand if the customer or employee is talking loudly, which is often an indication of being angry or upset. The quality of communication with the client can also be determined by setting the following metrics: interruptions, non-talk time, talk speed, talk time.
Besides call-centers, Transcribe Service can be useful in almost any field: education, law, e-commerce, and many others. For example, Amazon Comprehend Medical is a machine-learning-powered HIPAA-eligible service pre-trained to identify and extract health data from medical texts, such as prescriptions, procedures, or diagnoses.
It is difficult to imagine modern technologies without a service that can transform speech into text. And of course, Transcribe has analogues from other digital giants. However, it is worth noting that a large number of developers who have leveraged Amazon service, admit a much higher quality and accuracy compared to similar solutions provided by the current market.