Google Cloud Speech-to-Text

Score8.3 out of 10

55 Reviews and Ratings

What is Google Cloud Speech-to-Text?

Speech-to-Text on Google Cloud is a tool used to convert speech into text using an API powered by Google’s AI technologies. The vendor states users can transcribe content in real time or from stored files; deliver a better user experience in products through voice commands; and, gain insights from customer interactions to improve service.

Categories & Use Cases

Media

Screenshot of audio transcription creation - Using the Speech-to-Text API from within the Cloud Console by creating an audio transcription is done in just a few steps. It can transcribe short, long, and streaming audio.

Screenshot of creating subtitles for videos using AI - Transcriptions with captions and subtitles can be added to existing content or in real time to streaming content. Google's video transcription model can be used for indexing or subtitling video and/or multispeaker content and uses similar machine learning technology as YouTube does for video captioning.

Screenshot of adding Speech-to-Text to apps - The video pictures covers how to add AI to an application without extensive machine learning model experience. The pretrained Speech-to-Text API lets users enable AI for applications.

Screenshot of Language, speech, text, and translation with Google Cloud API - The pictures displays a section of Google training course, where learners use the Speech-to-Text API to transcribe an audio file into a text file, translate with the Google Cloud Translation API, and create synthetic speech with Natural Language AI.

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Screenshot of audio transcription creation - Using the Speech-to-Text API from within the Cloud Console by creating an audio transcription is done in just a few steps. It can transcribe short, long, and streaming audio.

Satyam Pandey View profile

Associate software developer in Information Technology at Panamoure (51-200 employees employees)

Use Cases and Deployment Scope

I prefer Google Cloud Speech to Text for translating people's queries because my team members are from different countries, and I need to communicate with them effectively. So, it's good to understand their language and speak with them. Apart from that, I implemented its API in my various Python scripts to automate my virtual assistant in different languages. Its custom models and phrase hints improve the accuracy and maintain the process well. Sometimes I also used it for my YouTube video subtitles and podcasts. We can use it in many ways and enhance our capability to work in extreme conditions.

Pros

So, first of all it gives the answer or translates in real time which is awesome.
It has speaker diarization, which detects who spoke each segment. This is a great feature because it can track the number of people as well.
It has an automatic punctuation system that detects each punctuation mark, such as a dot and a comma, and places it in the text.
Lastly, it offers a variety of language translations, providing a global platform for interaction with people from different countries.

Cons

It has a limited accuracy in a noisy and accented environment so, it can be improved.
If there are 5+ people in a conversation, then the speaker diarization will fail. So, this can be enhanced.
There are limited emotions for voice, so these can be enhanced. We can add more emotions to the models and train them.

Return on Investment

It saved us a lot of time and money by eliminating the need to transcribe meetings, interviews, and general discussions.
If I talk about my office team, it gives me the power to understand the language of each member, and now I'm not forcing them to translate it into my language.
The best part is that it freed us to focus on other aspects, such as innovation, and elaborate on our thoughts, because now we don't have to worry about language; we just need to express our ideas.

Usability

Alternatives Considered

Microsoft Azure, OpenAI API and Amazon CodeWhisperer

Other Software Used

Microsoft Azure, Amazon Athena, OpenAI API

irfan shaik View profile

Technical Consultant in Information Technology at Numeric technologies inc (1001-5000 employees employees)

Use Cases and Deployment Scope

Transcribing customer support calls for quality analysis were made easier with Google Cloud Speech-to-Text where it transcribe the communication and help us in elevating the business smoothly. We also use certain configuration parameters like language,model,speaker etc and send an audio data as soon as this is sent the API will return us the transcribed text that way we can reduce maximum manpower and increase the productivity. Earlier creating the captions for the real time meeting seems to be very hard like post meeting if we would like to clarify any information we didn't have the captions available and we relay totally on the manual notebook entry but post this we can recheck the caption and fetch any information we needed. Easy to copy and secure it safe.

Pros

Transcribing customer support calls for quality analysis
Creating the real-time captions for meetings and webinar
Automate the documentations based on the speech API's
Streaming real-time transcription using streaming API's
Converting audio's to text from different languages is also easier

Cons

Integration outside of the google eco system is challenging here.
Google Cloud Speech-to-Text works only with active internet connection if the internet bandwidth is low it effect the transcription process and can lead to data inaccuracy.
In terms of the pricing also this is at higher range which all the companies cannot afford like small scale organisation if they would like to use the tool they would look over the price to make the decision. Reducing the price can increase the product usage more

Return on Investment

Right now it is very costly for any small company to afford price can be reduced
Extension to skype/webex can increase connectivity to multiple systems and capture the data efficiently
Multi language features is an great asset to this tool as it will help us to transcribe text of any language. More than 100 plus languages support
Customer support is also great who assist us whenever we face issue and gets resolved very fastly

Usability

Alternatives Considered

Amazon Transcribe

Other Software Used

Google Analytics, Google Ads, Palo Alto Networks Advanced Threat Prevention

Aaron Henderson View profile

Marketing Specialist in Marketing at MK Marketing (11-50 employees employees)

Use Cases and Deployment Scope

I do a lot of writing, and I do a lot of speaking. I want to keep records of both just in case I need to edit later, and with this Google product it is like carrying an old-fashioned dictaphone with you. Is this a bad thing? Nope - it's just another app that can solve a need without carrying a lot of equipment with you, and the lag time is good - meaning that there isn't a lot of lag.

Pros

deciphers tougher words
keeps up with my speech speed and patterns
maintains an accurate record of what is spoken

Cons

It could be faster - there is lag
I would like to see a different interface - just a personal thing
Better in more of a real time

Return on Investment

Ability to keep up with speech
Ability to translate - if that is your thing
Reduced noise cancellation would be good

Usability

Other Software Used

Google Ad Manager, Google Ads, Adobe InDesign

Maria Sergeeva View profile

UX and Content Designer in Marketing at Career Pathway Institute (51-200 employees employees)

Use Cases and Deployment Scope

We use it as an assistant while transcribing our customer interviews into text, which helps us save time and energy on transcriptions and allows us to focus more on complex and interesting tasks. We have also tried using the text-to-speech function to add audio to our interfaces and we found it very convenient.

Pros

Transcribe speech into text
Transcribe text into speech
Share transcriptions among the team members

Cons

It is very expensive when you start work with big files
It has some troubles with accents
Doesn't work good when some people speak simultaneously

Return on Investment

It reduced our budget for assistants who transcribed files manually
It speeds up the process, because we can have a transcriptions straight after the interviews
It increased accuracy, because AI makes the transcriptions for every second, and you can find the words which were said at specific time.

Usability

Alternatives Considered

Descript

Other Software Used

Notion, Adobe XD, ChatGPT

Pintu Prusty View profile

support engineer in Information Technology at dynacons system and solutions ltd (501-1000 employees employees)

Use Cases and Deployment Scope

We use Google Cloud Speech-to-Text in our company mainly to convert voice recording - like me1etings, customer calls, and voice notes—into written text. Is also capable of converting various sorts of audio sources to text, which is convenient for some who may have trouble hearing or are not present

Pros

Speech to text
Accuracy
Text format can be seen by all people in the meeting.

Cons

A feature that focuses on only the speaker.
Pricing is a bit on a higher side.
Depending upon your accent it can be hard but rarely

Return on Investment

Lets me record interviews quickly.
It should detect regional accents more accurately and adapt to local speech patterns.

Usability

Other Software Used

Microsoft Teams, AWS Lambda

IBM Watson Speech to Text

Azure AI Speech

Amazon Transcribe

Google Cloud Speech-to-Text

What is Google Cloud Speech-to-Text?

Categories & Use Cases

Media

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Use Cases and Deployment Scope

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Alternatives Considered

Other Software Used

Use Cases and Deployment Scope

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Other Software Used

Use Cases and Deployment Scope

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Alternatives Considered

Other Software Used

Use Cases and Deployment Scope

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Other Software Used

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