Amazon Transcribe vs. Azure AI Speech

Amazon Transcribe can be an excellent tool for businesses where being able to convert speech or audio to text, in a searchable and reportable form, would be useful. For a call center (inbound or outbound), the ability to have a rich transcription of each call (and being able to search it for keywords) is an incredibly valuable benefit. For business meetings, being able to turn a 60 or 90-minute call into a readable transcript to search or refresh yourself or others is a very large time saver which will help you work more efficiently. The software does offer many deeper integrations, such as being able to track script usage (for call centers) or interruptions, deviations, etc.. which would be very valuable to a management team and for training purposes.

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This service is well suited for scenarios where you need to integrate text-to-speech and/or speech-to-text into applications. Within our organisation, it is primarily used by students for development purposes to enable said functionality but is also used to provide accessibility to students who have hearing-related issues. Its multi-language support is also beneficial for our international students who have English as a second language and are therefore able to rapidly translate any text or speech that they do not understand.

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• It converts live recordings to text with few errors.
• It has powerful speech recognition models- it transcribes well even low quality audios.

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• APIs offered are very robust.
• Languages supported is far greater than most of its competitors.
• Integration with our custom apps was easy.
• Speech models that we created using neural voices were quite impressive.
• Translation services worked really well.
• Built in machine learning opens it to a lot more business use cases for the future.

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• It was not easy to bring Amazon Transcribe to life, but kudos to the vendor for the free support they offered.

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• More support for India regional languages and the ability to interpret Indian dialect.
• More detailed documentation with more coded examples to be available.

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I use Google Cloud Speech to Text and Amazon Transcribe. What makes Amazon Transcribe better for me is the accuracy of the audio-to-text conversion. I have found out that Amazone Transcribe is better at handling homophones, contractions, abbreviations, and acronyms. Another feature that makes Amazon Transcribe my No. 1 choice is its use of punctuation marks. I can also feed my own list of vocabulary into Amazon Transcribe to help me acquire better results.

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Azure Cognitive Speech Services is simple and the interface is not complicated even for those getting started with these customer services tools and the best voice recognition. Setting the platform dashboard preferences is also an easy process and with the ability to manage workflow and document management the system functions are stable and effective.

• Cost reductions in KYC automating our video approvals.
• Better customer service.
• A good base for building new products and services around speech to text.

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• It helps us catch requirements and make notes so that we don't forget when drawing out proposals.
• Also helps us with targeted pitches and helps save time.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info