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Amazon Transcribe makes it easy for developers to add speech to text capabilities to their applications. Audio data is virtually impossible for computers to search and analyze. Therefore, recorded speech needs to be converted to text before it can be used in applications. Historically, customers had to work with transcription providers that required them to sign expensive contracts and were hard to integrate into their technology stacks to accomplish this task. Many of these providers use outdated technology that does not adapt well to different scenarios, like low-fidelity phone audio common in contact centers, which results in poor accuracy. Amazon Transcribe uses a deep learning process called automatic speech recognition (ASR) to convert speech to text quickly and accurately. Amazon Transcribe can be used to transcribe customer service calls, automate subtitling, and generate metadata for media assets to create a fully searchable archive.

UniScribe is a platform that helps users quickly extract key information from lengthy local audio and video files or YouTube videos by converting them into text, empowered by AI. Features: - Faster conversion of local audio and video files or YouTube videos to text using an optimized Whisper model. - Automatic generation of summaries, mind maps, and key Q&A. - Supports exporting text content in various formats, such as .txt/.pdf/.docx/.srt/.vtt/.csv. Use Cases: - Journalists and Writers: To transcribe interview recordings into text for easier quoting and editing. - Students and Academics: To transcribe lectures, seminars, or meetings for easier note-taking and research. - Market Researchers: To transcribe audio data from focus groups and interviews for analysis. - Legal Professionals: To transcribe court records, testimonies, and client interviews for legal document preparation and research. -Content Creators and Producers: To transcribe media content for blog posts