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Amazon Transcribe features and reviews of 2020

Amazon Transcribe is AWS’s machine learning service that allows customers to convert speech-to-text accurately and quickly using Automatic Speech Recognition (ASR).

Overview

Amazon Transcribe voice recognition software uses advanced machine learning to convert audio inputs to text. The technology is applied in many business models including generation of subtitles and text-based analysis on video and audio content. 

Businesses can use it to transcribe voice-based calls for their customer care service. They can extract important phrases from speeches and carry out sentiment analysis. The software integrates with other Amazon services to accept voice input in a certain language, translate into another language, and give out a voice output. In other words, it allows multi-lingual speech transcription in about 31 languages and streaming transcription in six languages. 

Amazon Transcribe is also used to perform indexing and text-based search in video and audio libraries. It handles speech and acoustic attributes such as variations in speaking rate, volume, and pitch. Albeit, audio signals like overlapping speakers, background noise, language changes within one file, and accents can affect the quality of the output. Constant updates are being carried out to ensure stability in such cases.

This AWS service uses Automatic Speech Recognition (ASR) to provide accurate and fast transcription. The number of transcriptions that a user can run is limited to 100 per time. So, once users reach the limit,  they must wait for at least one slot to complete running before a new one starts running. Albeit, Amazon Transcribe allows one to queue the inputs such that when a slot is available, a new one starts to run.

Product Details

Amazon Transcribe voice recognition software mimics the quality of manually transcribed contents but takes only a fraction of the time. Users don’t have to be overly conscious of their speech tones for the software to pick when they’re asking questions or exclaiming. It adds formatting and punctuations automatically to make the transcript easy to read.

Amazon Transcribe voice recognition software helps users to stream their transcriptions with a secure connection. So, when they send live audios to the software, they get a stream of text in real-time. Lawyers use this feature in the courtroom to make real-time annotations. It’s also used to transcribe video game chats and real-time subtitles for live broadcasts.

Amazon Transcribe voice recognition software lets users add custom words to their vocabulary. Apart from the base vocabulary, the software allows users to add new words such as people’s names, product names, and technical terms. The ability to add domain-specific words makes it easy to transcribe voice recordings in that field more accurately. That’s why it’s suitable for transcription of doctor-patient consultation.

Once a user adds medical jargon to the software’s vocabulary, it becomes easier to transcribe medical and pharmacological terms for medical documentaries and teaching. It aids transcribing lessons into medical notes.

Hence, HIPAA compliant software solutions can benefit from Amazon Transcribe. Users can easily integrate this voice recognition software into any system that uses a microphone or any clinical documentation apps. Developers can also integrate Amazon Transcribe with other AWS software to extract medical information like medication, condition, dosage, frequency, and strength. 

Amazon Transcribe voice recognition software is compatible across devices that use on-device microphones like mobile phones, tablets, PCs, and IoT. It can tell the difference in quality in each audio stream and select the appropriate acoustic models for their transcription. Plus, developers can use their apps to call Transcribe API to have access to the speech-to-text conversion capability. These API calls take a maximum of four hours or 2GB per batch service.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          

Amazon Transcribe voice recognition software allows users to filter the vocabulary in a recording. When a user specifies a list of vocabulary that they don’t want to appear in the text, such as offensive or profane words, the software takes them out of the transcript automatically.

Amazon Transcribe voice recognition software recognizes multiple speakers through speaker identification or diarization. It allows users to transcribe an audio recording that has between two and ten speakers. If the number of speakers specified corresponds to the actual number of speakers in the input, the transcription will be more accurate.

The software recognizes each speaker’s voice in an audio recording. So, in scenarios like interviews, lectures, or press conferences, one can identify the moderator and the speaker per time. It’s also useful for transcribing meetings, phone calls, and television shows. Amazon Transcribe gives time-stamped texts. So users can edit or add to the content and easily trace a word or phrase in the original audio or video recording.

Amazon Transcribe voice recognition software can be instructed to identify and redact personally identifiable information (PII) that might be sensitive. It automatically identifies these elements from any supported language transcript. So, contact centers can edit and share the transcript for customer care training or customer experience.

Amazon Transcribe voice recognition software automatically annotate transcripts with channel labels. In the case of audio files with multiple channels, the software can separate them into transcriptions that show what channel they came from. Take the case of an interviewer who’s on a different channel from the interviewee, for instance.

The resulting transcript is a combination of their individual transcripts. The same scenario goes for a transcript that contains more than two users. Each speaker’s start time determines their utterances. Even when the utterances from each channel’s input overlap, they won’t overlap in the transcript output.

Amazon Transcribe voice recognition software requires users to be clear in their speeches to produce a more accurate transcript. The way users pronounce the added custom vocabulary determines the speech recognition output. The software recognizes the words as texts. Albeit, if the user pronounces it wrongly, the output becomes inaccurate.

The user can solve this issue by providing a pronunciation for the custom word and adding other variants of that word. In that way, the software recognizes all the variants in speeches.

Amazon Transcribe voice recognition software allows users to customize the quality level of their transcription output. By default, Amazon Transcribe produces only transcripts with the highest level of confidence score in terms of quality. However, the software allows users to request additional lower-confidence level transcripts.

Recap

According to some users, Amazon Transcribe voice recognition software reduces the need to perform any manual changes. It supports several audio formats and can identify the number of speakers in audio input with timestamps to follow the conversation.