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 Many of these providers use outdated technology that does not adapt well to different scenarios, like low-fidelity phone audio common in contact centers, which results in poor accuracy.
Product | Market Share (%) |
---|---|
Amazon Transcribe | 11.8% |
Microsoft Azure Speech Service | 22.1% |
Deepgram | 18.2% |
Other | 47.89999999999999% |
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.
Author info | Rating | Review Summary |
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Senior Software Developer at a tech vendor with 10,001+ employees | 4.0 | I use Amazon Transcribe to efficiently convert voice to text for various projects, benefiting from its scalability and cost-effectiveness. However, it struggles with processing background noise, and improvements in that area would be valuable. |
AWS Senior Engineer at Indra | 4.0 | No summary available |
DevOps Engineer at Goftech Support | 4.5 | No summary available |
Owner at a non-profit with 1-10 employees | 3.5 | No summary available |
Architect at a tech company with 201-500 employees | 4.0 | No summary available |