Amazon Transcribe vs. Amberscript vs. Trint

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.

Incentivized

Amberscript is great for transcribing individual audio (or video) files that reside on your computer. The ability to view and edit the text of the text file (to correct or remove data that you don't want to be shared) before the output is a great option. I feel it may be limited in the ability to transcribe live audio records such as phone calls or meetings, where we would find it very useful to have immediate access to a transcript (for coaching or sharing purposes). I feel the needs are more designed as a solution for pre-existing audio/video files versus working in real-time.

Incentivized

It consequently translates sound from all record designs and produces a shareable and editable transcript. The interface of Trint is decent and works really hard in interpreting the content. It can also be used when taking an interview of an individual from a different language background. Here and there the record of certain dialects contains botches which are then rectified by the actual persons.

Incentivized

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

Incentivized

• Automated Speech to text transcribing
• Video and Audio file to text data file conversion

Incentivized

• User friendly interface
• Value for money
• Seamless to transcribe from audio
• Performance is quick give results fast

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

Incentivized

• There does not appear to be a way to transcribe live audio (such as a live meeting or live phone call)

Incentivized

• No choice for erasing the records whenever you have utilized them.
• The API likewise needs a great deal of work to be finished.
• The limitless provisions are extremely less.

Incentivized

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.

Incentivized

I feel that Amazon Transcribe was much more feature-rich, allowing for a much more real-time solution, whereas Amberscript is great for transcribing existing call recordings (or video files) to a rich text file. Amazon Transcribe will do both, while Amberscript only does the latter. For our business, this was a significant feature loss for Amberscript.

Incentivized

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

Incentivized

• Having an automated speech-to-text conversion allows us to reduce human hours, which would normally take notes or have to review long audio files.
• Being able to transcribe multiple call recordings into a searchable text format allows for coaching of issues in a much more efficient format than an audio recording.

Incentivized

• Save time and money
• Quick results help us to focus on different work