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From call audio to CSAT: Mapping contact center sentiment to CX signals
TL;DR: Manual QA teams sample 2–5% of contact center calls, leaving more than 95% of customer interactions unscored. Transcript errors propagate directly into your sentiment layer: a single substitution that flips "can't" to "can" inverts the sentiment signal before your classifier runs, making transcription quality a direct input to CSAT reliability. To automate quality assurance at 100% coverage, solve the transcription layer first. This playbook maps the audio-to-CSAT pipeline, explains where transcript errors compound into false QA scores, and shows the four production steps required to scale sentiment analysis across noisy, multilingual Business Process Outsourcing (BPO) environments.
Integrating speech-to-text into your EHR: epic, athenahealth and FHIR
TL;DR: The real engineering work in EHR speech integration is mapping unstructured audio payloads to the correct FHIR resources, managing SMART on FHIR OAuth 2.0, and building resilient async write pipelines that survive rate limits and EHR downtime. On Growth and Enterprise plans, customer data is never used for model training, which is an important baseline control for any clinical pipeline handling PHI. The architectural patterns in this guide apply whether you choose a managed STT API or build the transcription layer yourself.
European-language speech-to-text: evaluating coverage and accuracy
TL;DR: Academic benchmarks fail to predict production STT performance in European business environments, where accented speech, code-switching, and telephony noise push real-world Word Error Rate well above what clean read-speech datasets suggest. Engineering and ML Leads evaluating STT infrastructure need three metrics standard benchmarks don't capture: real-world WER on accented audio, Language Adherence Violation Rate for code-switching performance, and total cost of ownership (TCO) including engineering toil for self-hosted GPU clusters. On Switchboard, the most demanding conversational telephone dataset, Solaria-3 ranks #1 ahead of AssemblyAI, ElevenLabs, Deepgram, Mistral, and Speechmatics: a concrete example of how production-relevant benchmarking changes the vendor picture. This guide provides the technical framework to run a statistically valid evaluation against your own audio distribution before committing to any vendor or build decision.
Here’s how speech-to-text AI can benefit your business today
Published on Jun 2, 2023
Speech-to-text AI is entering an exciting phase and becoming a commodity. By powering Audio intelligence, products like Gladia's Audio Transcription API create value for all businesses, from collaboration platforms to content studios to media companies to call centers.
Voice is the primary way we interact with the world. From virtual meetings to content studios and call centers, audio data is a goldmine of information for knowledge workers.
Audio Intelligence AI is the key to unlocking it. AI-powered tools, capable of transcribing, summarising, and enriching audio and speech data are becoming essential for businesses of all sizes looking to streamline their workflows, improve productivity, and enhance collaboration. Speech-to-text AI benefits more and more businesses every day.
Best part? The underlying tech is becoming truly accessible. While previous-generation tools were often discarded by companies due to poor quality, slow performance, and high costs, Speech AI is entering an exciting phase where its core component — audio transcription — is gradually becoming a commodity through state-of-the-art APIs.
Speech-to-Text AI benefits
In this post, we’ll explore some of the ways that Gladia’s Audio Intelligence API can help businesses across industries turn raw audio data into actionable knowledge.
Virtual Meetings
As online meetings became the new norm of our work lives, so did audio transcription — a rich source of insights into the number of participants and their sentiments, as well as the key talking points discussed. Beyond generating accurate transcriptions in seconds, AI voice tech can take notes and produce snapshot summaries optimized for sharing with the rest of the team and other stakeholders. What better way to keep everyone aligned while saving time?
Why should you consider an audio transcription API for your online calls and events:
Users can forget about taking notes while on-call and concentrate 100% on the meeting;
Ability to keep track and easily search for all valuable information over time;
Broader cognitive bandwidth to dedicate to more strategic and creative business decisions thanks to the extra time and information gained.
Learn more about the value of language AI for web conferencing platforms here.
Workspace Collaboration
Workspace collaboration platforms — think chat platforms, kanban board, Gantt chart tools, or any other solutions that help teams organize and share knowledge internally — can be equally enhanced with AI audio intelligence tech.
Platforms of this kind are defined by large volumes of multimedia files (messages, PDFs, URLs, voice memos, etc). By embedding audio intelligence features like topic classification, summarisation, and semantic search into your collaboration platform, you open up a range of new possibilities for the final user to exchange information more efficiently. For example, long meetings with clients or voice memos are translated almost instantly into actionable bullet-point summaries available to everyone in the organization.
Here’s what you gain with the help of AI:
Less time spent in meetings that can be automatically shared as a summary or a memo;
Cross-functional knowledge sharing made seamless;
Ability to connect dispersed sources of information, whatever the provenance file, for a more comprehensive overview of any given topic;
Higher user engagement as knowledge becomes easier to locate and act on.
Learn more about boosting your productivity and knowledge management practices with AI here.
Content Creation
Content creation can be a time-consuming process. Be it for videos, podcasts, or on-tape interviews, transcription is becoming one of the key prerequisites for efficient editing and successful distribution.
Thanks to Gladia’s speaker detection (diarization), compatible with any audio file, your transcriptions are not only accurate and quick to produce but also easy to read. We provide subtitle-ready output files to replace error-ridden automatic captions on YouTube and other video streaming or social media platforms. With our translation feature, supporting 99 languages (and counting!), your users can even aspire to reach a more international audience.
Work with Gladia if you want to help your users:
Spend less time transcribing and more time being creative with your content;
Produce high-quality, multilingual transcriptions that capture all the right keywords and boost their SEO ranking, be it with videos or podcasts;
Generate new content ideas thanks to topic detection and search, which makes it easy to connect and compare all your internal transcripts.
Learn more about the benefits of language AI for content platforms here.
Call Centers
Call center enterprises have been among the first to adopt automatic speech recognition (ASR) — and for a good reason. Given the high volume of calls, it is essential for customer support departments to get the right insights delivered to front-line operators fast to reduce the average handle time, improve efficiency and boost customer satisfaction. Gladia’s Speech AI can help with the above while guaranteeing security and privacy compliance.
Speech-to-text AI benefits in a nutshell:
Ability to capture every caller’s personal details and queries with 100% accuracy;
Improved first-call resolution and incident response rates as customer data is made available in real time;
More nuanced understanding of customer needs based on speaker identity and sentiment.
You can find a more detailed breakdown of our offer for call centers here.
Taking stock, Speech-to-text AI technology has numerous applications to help businesses improve their workflows and gain valuable insights into their customers’ needs. By harnessing the power of Audio Intelligence, businesses can save time, reduce errors, and improve collaboration and productivity by a margin.
About Gladia
At Gladia, we built an optimized version of Whisper in the form of an API, adapted to real-life use cases and distinguished by exceptional accuracy, speed, extended multilingual capabilities and state-of-the art add-ons, including speaker diarization and word-level timestamps.
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Read more
Speech-To-Text
From call audio to CSAT: mapping contact center sentiment to CX signals
Speech-To-Text
Integrating speech-to-text into your EHR: Epic, athenahealth and FHIR
Speech-To-Text
European-language speech-to-text: evaluating coverage and accuracy
From audio to knowledge
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