Automatic interview transcription
Long-form interviews were transcribed automatically through Speak AI, producing accurate transcripts that the editorial team could work with immediately. No more hours of manual transcription per interview.
Jason Winders and the communications team at Western University use Speak AI to transcribe long-form interviews, identify key themes, and convert conversations into published articles, saving hours of manual work on every piece of content.
Western University is one of Canada’s top research-intensive universities, with a communications team responsible for producing a steady stream of editorial content. Jason Winders, Director of Editorial Services, and his team regularly conduct long-form interviews with faculty, researchers, and community members as the raw material for articles, stories, and institutional communications.
The interview-to-article pipeline is inherently time-consuming. Each interview needs to be transcribed, reviewed for key quotes and themes, and then shaped into a polished piece of content. Manual transcription alone can take four to six hours for every hour of recorded conversation. For a team producing content regularly, this transcription bottleneck consumed a significant portion of available editorial time.
Western University’s communications team adopted Speak AI to automate transcription and accelerate the interview-to-article production pipeline.
Long-form interviews were transcribed automatically through Speak AI, producing accurate transcripts that the editorial team could work with immediately. No more hours of manual transcription per interview.
Speak AI automatically identified keywords and themes from each interview, giving the editorial team a head start on finding the most important content for their articles without manually reviewing every line.
With automatic transcription handling the documentation, team members could focus entirely on the conversation during interviews. No more divided attention between listening and note-taking.
The combination of instant transcripts and automated theme identification meant the team could move from interview to published article significantly faster, increasing their content output without adding headcount.
Editorial teams reclaim hours per interview: Automated transcription eliminated the biggest time sink in the interview-to-article pipeline, letting the team focus on writing and storytelling instead of typing.
Automatic theme identification accelerates editorial decisions: Instead of manually scanning transcripts for quotable moments, the team got AI-identified keywords and themes that pointed them to the strongest content immediately.
Better conversations happen when you are not taking notes: With transcription handled automatically, interviewers could be fully present in conversations, leading to better questions and richer content.
University communications teams can scale content production: By removing the transcription bottleneck, the team could produce more published content from the same number of interviews without adding staff.
Whether you run a university communications team, corporate editorial department, or content agency, Speak AI helps you transcribe interviews, identify themes, and produce content faster. Book a demo or start exploring the platform today.
Create a free account and start a 7-day trial. Upload interviews, get automated transcripts, explore keyword and theme identification, and see how Speak AI fits your editorial workflow.
Talk to our team about your content production needs. We will walk through how transcription, theme identification, and analysis can work for your editorial process.
