Remote and hybrid meetings have become a regular part of working life for organisations of all sizes. Teams may be spread across several offices, countries and time zones, with employees joining conversations from meeting rooms, home offices and mobile devices.
For businesses developing meeting platforms, automatic speech recognition (ASR) can make these conversations easier to follow, record and review. Live captions can help participants understand what is being said, while searchable transcripts allow employees to revisit discussions without listening to entire recordings.
However, recognising speech accurately during a meeting is not always straightforward. Participants may speak with different accents, interrupt one another or use specialist terminology. Background noise, poor microphones and unstable internet connections can also affect transcription quality.
Remote and hybrid meetings are now a regular part of working life. Teams are spread across offices, countries and time zones. Employees join from meeting rooms, home offices and mobile devices.
This guide compares five automatic speech recognition (ASR) providers for businesses that build or buy meeting platforms. It covers accuracy, latency, speaker diarisation, language coverage, integration and cost.
Why Is Meeting Transcription Hard?
Several factors make meeting transcription harder than general speech recognition:
- Participants speak with different accents and first languages.
- People interrupt one another and talk at the same time.
- Meetings include specialist terminology and product names.
- Background noise, poor microphones and unstable internet connections reduce audio quality.
The following five automatic speech recognition providers offer capabilities relevant to remote and hybrid meeting platforms. Each supports different technical requirements, making the most suitable choice dependent on the application’s intended users and operating environment.
The Best Automatic Speech Recognition Tools for Remote and Hybrid Meeting Platforms
| Rank | Provider | Key Strengths | Suitable Applications |
| 1 | Speechmatics | Multilingual recognition, live transcription, accent coverage and flexible deployment | International meeting platforms, live captions and enterprise transcription |
| 2 | Microsoft Azure AI Speech | Real-time speech recognition, language customisation and Azure integration | Enterprise meeting software and Microsoft-based applications |
| 3 | Deepgram | Streaming transcription, low-latency applications and developer APIs | Live meeting captions and interactive voice applications |
| 4 | Google Cloud Speech-to-Text | Managed cloud infrastructure, language support and speech recognition APIs | Cloud-based meeting platforms and recorded meeting transcription |
| 5 | AssemblyAI | Speech recognition, speaker diarisation and audio intelligence | Meeting archives, transcript search and conversation analysis |
1. Speechmatics
Speechmatics provides automatic speech recognition technology for organisations developing applications that need to convert spoken language into text. Its support for real-time and recorded audio makes it relevant for remote and hybrid meeting platforms that require both live captions and post-meeting transcripts.
How Does Speechmatics Handle Different Accents?
International teams include participants with different accents and first languages. Meetings may involve rapid conversation, interruptions and specialist vocabulary. A transcription system must handle these variations without requiring participants to change how they speak.
Speechmatics places considerable emphasis on multilingual speech recognition and accent coverage. This makes it a strong fit for meeting platforms used by international businesses and geographically diverse teams.
Does Speechmatics Support Live Captions?
Yes. The platform supports real-time transcription, so applications can display recognised speech while a meeting is taking place. Developers can use this for live captions, accessibility features and other functions that depend on a continuous stream of text.
Speaker diarisation is another relevant capability. It helps distinguish between different speakers in a recording, although performance can depend on audio quality and how participants are captured.
In hybrid meetings, where several people may share a microphone, reliable speaker separation can be particularly challenging.
Deployment flexibility may also influence the choice of ASR provider. Some organisations prefer managed cloud services, while others have specific requirements governing data processing or infrastructure.
Speechmatics offers different deployment arrangements, including options for organisations seeking greater control over their speech recognition environment.
This can be relevant for enterprise meeting platforms serving customers with demanding security or operational requirements.
Key Services
- Speechmatics provides real-time automatic speech recognition, batch transcription and multilingual speech-to-text APIs.
- Its capabilities include speaker diarisation, punctuation and transcription across different languages and audio environments.
- The company also offers deployment options suitable for enterprise applications and integration into third-party software platforms.
Why Choose Them
- Speechmatics is a strong option for meeting platform developers serving international teams and multilingual organisations.
- Its focus on accent coverage and multilingual recognition may be particularly useful where participants speak different varieties of English or communicate in several languages.
- The availability of live and batch transcription also makes it relevant for platforms that provide both real-time captions and searchable meeting records.
- Businesses with specific infrastructure requirements may find its deployment flexibility useful when evaluating enterprise speech recognition providers.
For more information about multilingual ASR, live meeting transcription and speech-to-text API integration,Visit Speechmatics.
2. Microsoft Azure AI Speech
Microsoft Azure AI Speech is a cloud-based speech recognition service within the Azure platform. It provides tools for developers building applications that convert spoken language into text, including software used for meetings and business communication.
Key Services
Microsoft Azure AI Speech provides real-time speech-to-text, batch transcription and speech recognition APIs.
Its capabilities include language support, recognition customisation and integration with other Azure services.
The wider speech platform also provides tools for developing voice-enabled applications.
Why Choose Them
Azure AI Speech is a relevant choice for meeting platform developers already using Microsoft cloud technologies.
Its integration with Azure infrastructure may be useful for organisations managing transcription alongside other enterprise services.
The platform may also suit applications requiring speech recognition customisation for specialist terminology or particular business environments.
Visit Microsoft Azure AI Speech
3. Deepgram
Deepgram provides speech recognition APIs and related voice AI technologies for developers building applications that process spoken language.
Who Is Deepgram For?
Deepgram provides speech recognition APIs and voice AI technologies. Its streaming transcription capabilities suit remote meeting platforms that need to display text while participants are speaking.
Why Does Latency Matter for Live Captions?
Live transcription has different technical requirements from processing recorded audio. A meeting platform must receive audio, send it for recognition and display the text quickly enough for captions to remain useful. If the delay is too long, participants struggle to follow the conversation.
How Fast Is Deepgram’s Streaming Transcription?
Deepgram offers streaming speech-to-text APIs built for responsive transcription. These suit live captions, communication tools and other software where recognised text must appear during an ongoing conversation.
Deepgram provides transcription features such as speaker diarisation, although the availability and suitability of individual capabilities depend on the selected model and processing method.
Its developer-focused approach may appeal to teams that want to integrate speech recognition directly into their own meeting products.
Key Services
- Deepgram provides streaming speech-to-text, pre-recorded transcription and developer APIs for voice applications.
- Its speech recognition services include features such as speaker diarisation and transcript formatting, depending on the model and configuration.
- The company also offers related voice AI technologies for conversational applications.
Why Choose Them
- Deepgram is a relevant option for developers building meeting platforms where responsive live transcription is an important requirement.
- Its streaming APIs may be particularly useful for live captions and other features that depend on low-latency speech recognition.
- The platform may also suit businesses developing wider voice-enabled communication products.
4. Google Cloud Speech-to-Text
Who Is Google Cloud Speech-to-Text For?
Google Cloud Speech-to-Text is a managed ASR service running on Google’s cloud infrastructure. Developers use its APIs to convert audio into text in applications that process live conversations, recorded meetings and other spoken content. Google Cloud Speech-to-Text is a managed automatic speech recognition service that allows developers to convert audio into text through Google’s cloud infrastructure.
Its speech recognition APIs can be used in applications that process live conversations, recorded meetings and other spoken content.
For remote and hybrid meeting platforms, cloud integration is often an important consideration. A meeting application may need to manage audio streams, store recordings, generate transcripts and make those transcripts available to users.
Does Google Cloud Offer Speaker Diarisation?
Yes, depending on the recognition model and configuration. Google Cloud offers speaker diarisation and automatic punctuation. These features produce more readable transcripts, but performance should be tested with realistic meeting recordings.
What Should Developers Check Before Choosing Google Cloud?
- Regional availability of the service
- Usage limits for expected transcription volumes
- Costs at the expected scale
- Integration with other Google Cloud products for storage, access controls and analytics
Google Cloud Speech-to-Text features
- Speech recognition APIs for streaming and recorded audio
- Multilingual recognition
- Automatic punctuation and speaker diarisation, depending on the model
- Integration with Google Cloud storage, development and analytics products
Why Choose Them
- Google Cloud Speech-to-Text is a relevant choice for meeting platform developers already using Google Cloud infrastructure.
- Its managed service may appeal to teams that want to integrate speech recognition into existing cloud applications.
- The platform may also suit businesses developing meeting transcription alongside wider data processing and analytics workflows.
Visit Google Cloud Speech-to-Text
5. AssemblyAI
Who Is AssemblyAI For?
AssemblyAI provides speech recognition and audio intelligence APIs. It suits developers working with recorded conversations, meeting platforms that offer searchable transcripts and products built around conversation analysis.
Why Do Organisations Need Post-Meeting Transcription?
Live captions help during a meeting. After the meeting, employees often need to:
- Find a particular decision
- Revisit an explanation
- Identify sections related to a specific project
A transcription service provides the text that supports these functions.
What Is Audio Intelligence?
AssemblyAI offers speech-to-text alongside features designed to extract additional information from audio. Developers can use this to organise recorded discussions or build tools for analysing conversations.
How Good Is AssemblyAI’s Speaker Diarisation?
Speaker diarisation identifies changes between speakers, which makes transcripts easier to read and review. Developers should test it carefully when recordings contain overlapping speech or several people using the same microphone.
Is AssemblyAI Easy to Integrate?
The company provides developer tools and documentation for integrating its services into software applications. Transcription and audio analysis features are available through one API platform, which can simplify development.
Businesses should still examine the cost and suitability of individual features, particularly when processing large volumes of recorded meetings.
AssemblyAI: Key Services
- Speech-to-text APIs
- Audio intelligence capabilities
- Transcription and speaker diarisation
- Features for analysing recorded conversations
- Support for meetings, interviews, media recordings and other spoken content
AssemblyAI: Pros at a Glance
- Strong focus on post-meeting transcripts and conversation analysis
- Useful for searchable meeting archives
- API-based transcription without building in-house speech recognition
How to Choose an ASR Provider for Remote and Hybrid Meetings
How Important Is Recognition Accuracy?
Very. Meetings include several speakers, interruptions, specialist terminology and varying microphone quality. Test providers using recordings that reflect actual users rather than relying entirely on published accuracy figures.
How Much Latency Is Acceptable for Live Captions?
Live captions must appear quickly enough for participants to follow the discussion. A provider may be accurate but still unsuitable if the delay between speech and text is too long.
What Is the Difference Between Speaker Diarisation and Speaker Identification?
Speaker diarisation recognises that two sections of audio come from different speakers. It does not establish their names. Hybrid meetings make this harder because several participants may share one microphone. Platforms achieve better results when individual audio channels are available.
How Do You Evaluate Language and Accent Coverage?
International organisations hold meetings with speakers from several countries, sometimes in more than one language. Check the provider’s language capabilities and test recognition with representative speakers.
How Does Background Noise Affect Transcription?
Participants join from busy offices, public spaces and home environments. Background sounds reduce audio quality. Evaluate each ASR service using the recording conditions the application is likely to encounter.
What Integration Capabilities Should You Check?
Meeting platforms need to process continuous audio streams, manage connection interruptions and display partial transcription results. Review developer documentation, SDK availability and API reliability, since these affect implementation time.
What Security and Privacy Questions Should You Ask?
Conversations may contain personal information, financial details or commercially sensitive material. Examine how audio and transcripts are processed, stored and retained. Review the provider’s security controls and contractual arrangements.
Does Deployment Flexibility Matter?
Some enterprise customers prefer managed cloud services. Others require specific processing locations or greater control over infrastructure. Confirm the provider supports the deployment model the customer needs.
How Should You Evaluate Pricing and Scalability?
A platform supporting thousands of meetings processes substantial audio every month. Total cost includes transcription usage, additional features, storage and engineering resources to maintain the integration.
What Is the Best Way to Test Providers?
Test several providers with realistic meeting audio. A pilot under actual meeting conditions establishes which service meets both technical and commercial requirements before a wider deployment.
Frequently Asked Questions
What is automatic speech recognition in meeting platforms?
Automatic speech recognition is technology that converts spoken language into written text. Meeting platforms use ASR to generate live captions, create transcripts and support features that help users review recorded conversations. The technology is integrated through an API or another supported development interface.
Can ASR tools transcribe meetings in real time?
Yes. Many ASR providers offer streaming transcription that processes audio while participants are speaking. This allows meeting platforms to display captions during a conversation. The delay between speech and text varies depending on the provider, audio connection and recognition configuration.
How does speaker diarisation work in meeting transcription?
Speaker diarisation analyses audio to distinguish between different speakers. It divides a transcript into sections associated with separate voices, making conversations easier to follow. It does not necessarily identify speakers by name, and accuracy can be affected by overlapping speech or shared microphones.
Are ASR tools accurate when participants have different accents?
ASR tools can recognise speech from people with different accents, but accuracy varies between providers and recording conditions. Some systems are designed with particular emphasis on multilingual and accent-diverse speech recognition. Developers should test transcription using speakers who reflect the platform’s intended audience.
Can automatic speech recognition handle hybrid meetings?
Yes. ASR works for hybrid meetings involving remote participants and people sharing a physical room. Audio captured through a shared microphone makes speaker separation more difficult. Microphone placement, audio quality and the availability of separate audio channels affect transcription results.
What is the difference between ASR and an AI meeting assistant?
ASR converts spoken language into text. An AI meeting assistant may use transcription alongside other technologies to generate summaries, identify action points or organise meeting information. ASR provides the underlying transcript, but additional processing is generally needed for more advanced meeting analysis features.
How should businesses evaluate ASR providers for enterprise meetings?
Businesses should compare providers using representative meeting recordings and realistic technical requirements. Important factors include transcription accuracy, latency, speaker diarisation, language coverage, integration options, security and processing costs. A pilot involving actual meeting conditions helps establish which service is most suitable before wider deployment.
