Amazon Transcribe vs Microsoft Azure Speech Service comparison

Amazon Transcribe makes it easy for developers to add speech-to-text capability to their applications. Audio data is virtually impossible for computers to search and analyze. Therefore, recorded speech needs to be converted to text before it can be used in applications. Historically, customers had to work with transcription providers that required them to sign expensive contracts and were hard to integrate into their technology stacks to accomplish this task. Many of these providers use outdated technology that does not adapt well to different scenarios, like low-fidelity phone audio common in contact centers, which results in poor accuracy.

Amazon Transcribe uses a deep learning process called automatic speech recognition (ASR) to convert speech to text quickly and accurately. Amazon Transcribe can be used to transcribe customer service calls, to automate closed captioning and subtitling, and to generate metadata for media assets to create a fully searchable archive. You can use Amazon Transcribe Medical to add medical speech to text capabilities to clinical documentation applications.

Easily add real-time speech-to-text capabilities to your applications for scenarios like voice commands, conversation transcription, and call center log analysis.

Tailor your speech recognition models to adapt to users’ speaking styles, expressions, and unique vocabularies, and to accommodate background noises, accents, and voice patterns.

Build smart apps and services that speak to users naturally with the Text to Speech service. Convert text to audio in near real time, tailor to change the speed of speech, pitch, volume, and more.

Give your application a one-of-a-kind, recognizable brand voice using custom voice models. Simply record and upload training data, and the service will create a unique voice font tuned to your recording.