Transcription APIs Explained: How Developers Turn Audio Into Usable Text

Key Takeaways: 

• Transcription APIs enable developers to convert spoken audio into searchable, structured text, so they don’t have to build complex speech-to-text systems from scratch. 
• Businesses that integrate transcription APIs can analyze a vast volume of audio with added insights such as sentiment, tone, and conversational context.  

How are you managing all of the audio in your business? From customer calls and C-suite meetings to voice agents and live streams, you need a way to manage and analyze the spoken data in your organization. 

Audio is hard to search and even harder to use at scale. Unless, of course, you convert it into text. Transcription APIs are a helpful tool for developers to build a speech-to-text system that’s fast and accurate. Learn how transcription APIs work and why they’re such a game-changer for developers. 

In this guide:

• What Is a Transcription API, and How Does It Work?
• Common Use Cases for Transcription APIs
• The Benefits of Transcription APIs
• Turn Raw Audio Into Real Business Value
• Frequently Asked Questions

What Is a Transcription API, and How Does It Work? 

With the help of artificial intelligence (AI), transcription APIs automatically convert spoken audio into text via cloud-based services. Rather than building a speech-to-text system in-house, developers can leverage third-party speech-to-text models to turn audio recordings or live streams into readable transcripts quickly and efficiently.

Third-party transcription APIs are built with developers in mind. Apps integrate with these APIs to transcribe conversations at scale, whether through live audio streams or recorded file bundles. And most services accept a variety of audio and video formats, like WAV and MP4.

Developers can then usually integrate the transcription API directly into their own workflows. For example, one way to use a transcription API is to: upload recordings of customer calls, use the API to output a JSON transcript of the conversation, and send that transcript to other tools for sentiment analysis or topic flagging.

Here’s how the general workflow works:

• An API key is used to verify access.
• The API processes either pre-recorded/uploaded files or a live audio stream.
• Automatic speech recognition (ASR) and natural language processing (NLP) are used to interpret speech.
• A written transcript is produced (usually in JSON format).

The Technical Workflow

Most transcription APIs use speech-to-text technologies to convert audio recordings into text. First, the audio will usually undergo a “cleansing” step that minimizes background noise or distortions that could impact analysis. The API then converts audio signals into frequency information. (This is called a spectrogram.)

Next, the speech-to-text model chunks the spectrogram into phonemes. (Phonemes are units of sound that can differentiate one word from the next.) The model then uses AI to analyze phonemes within the context of the conversation to identify the words and phrases they correspond to. 

There’s more to it than that, though. It’s not just the words that were spoken that matter, but also the context around them. Modulate’s Velma adds intelligence to your transcripts with features like speaker diarization, timestamps, and proper punctuation and formatting so your transcripts are easy to read.

Common Use Cases for Transcription APIs

Use cases for transcription APIs span nearly every situation where a developer wants to search or analyze spoken audio content. 

Common examples include: 

• Call center intelligence - Understanding customer sentiment, compliance, or agent coaching audio from call centers. 
• Meeting transcription - Creating searchable transcripts for internal meetings, board meetings, or interviews. 
• Virtual assistants - Enabling natural language voice input that’s converted to text for downstream AI analysis. 
• Media editing and publishing - Creating podcast or media show transcripts for editing, publishing, or accessibility. 
• Financial and legal transcription - Recording and monitoring calls for compliance and fraud prevention in financial services, healthcare, insurance, and other regulated industries. 

The Benefits of Transcription APIs

There are many benefits to adding transcriptions to your workflows. They create a record of what you said during a meeting and also improve customer accessibility. However, setting up voice-to-text on the technical side can be difficult, which is why transcription APIs are such a game-changer for developers. 

Not all transcription APIs are created equal. But when you buy into a mature solution, good things happen. In addition to spending less time cleaning up transcripts, your developers will:

• Reduce time to value: Developers won’t need to spend months building their own transcription stack. A transcription API allows you to add speech-to-text to your app, platform, or workflow much faster.
• Easily scale production: Transcription needs can scale rapidly, particularly if your volume of calls, meetings, streams, or uploaded files balloons. Third-party APIs are designed to handle real-time and batch processing at scale so your team doesn’t have to worry about that heavy lifting.
• Leverage advanced features: Transcription APIs can come with features your developers would be hard-pressed to build alone. These extras can include speaker diarization, timestamps, punctuation, multi-language support, different accents, and more formatting capabilities to make transcripts easier to read and use.

Having a transcription API will save developers a ton of time. But you’ll still need smart people on your team who can manage the integration. Developers will be responsible for privacy, security, and upkeep just like they would with any API. Many teams find utilizing an API much easier than building a full fledged speech-to-text tool from scratch.

Turn Raw Audio Into Real Business Value

Audio transcription APIs convert spoken language into searchable, structured text. Rather than building this capability in-house from scratch, you can start with a purpose-built API from Modulate.

Velma Transcribe is Modulate’s speech-to-text API that can transcribe audio files as well as audio streamed in real-time. Velma Transcribe turns spoken conversations into clean, structured transcripts that can be plugged into your apps, analytics processes, and voice-enabled products. 

Velma Transcribe uses the same core technology that powers Modulate’s full Velma voice intelligence platform. Tasked with performing speech-to-text transcription with high accuracy, Velma Transcribe is one of the Dynamic Ensemble Blocks (DEBs) that comprise Modulate’s Ensemble Listening Model (ELM). Modulate’s proprietary ELM architecture routes speech through many AI models at once to understand every component of speech at the same time, processing the words people say while also analyzing tone, pacing, and conversational context to help teams better understand their conversations. 

We built Velma Transcribe to handle the messiness of real-world conversations, like overlapping speakers, accents, and background noise. It’s the most accurate and affordable transcription API service in its class. 

Get a transcription API that’s ready for production: Request a demo of Velma Transcribe. 

Frequently Asked Questions

How does transcription differ from captioning?

Transcription is the process of converting speech into text. Transcripts are typically used as a searchable/documentable record later on. Captioning is intended to be displayed on screen in real time, usually during live streams or recorded video content. 

Because of the added requirement for precise timing and onscreen readability, captioning files can be more difficult to work with. Most “streaming” STT APIs can be used for both transcription and captioning, including Modulate’s Velma Transcribe. Check with your transcription API provider to see if theirs supports both formats. 

Can I use a transcription API for compliance/legal records?

Yes. Transcription APIs can be used to create machine-generated records of conversations that can easily be searched and reviewed for compliance monitoring, internal record keeping, and more. 

Keep in mind that transcripts generated with AI will not be 100% accurate and shouldn’t be used for official legal documents without fact-checking. Many businesses choose to have employees fact-check their transcripts or keep the original audio on file in case a conversation is called into question.

How do transcription APIs handle code-switching/mixed-language conversations?

This will vary depending on the transcription API. Some services are designed to handle dozens of languages and various accents, while others have a very limited language scope. If your company has an international team or clients from around the world, seek out transcription services that are trained on diverse speech data and support a wide variety of languages.

How accurate are transcription APIs? 

The accuracy of transcription APIs depends on a number of factors. Audio quality, accents, and background noise can cause speech recognition software to fail to interpret words correctly. 

The sophistication of the speech-to-text model your provider uses also plays a large role. Many modern APIs report WERs (word error rates) of less than 10% under ideal testing conditions. Velma Transcribe by Modulate currently has an average WER of 7-8% on datasets like AMI IHM and Earnings 22 which focus on conversation content - roughly half the error rate of other leaders. (Deepgram, Google, and NVIDIA all average 14-15% WER on the same datasets.)