Keyterm Filtering API: Reduce false positives in speech-to-text transcription by verifying keyterms.

The core weakness of many powerful Speech-to-Text (STT) services is their susceptibility to contextual over-optimization. When developers use built-in keyword or keyterm boosting features to ensure the recognition of critical phrases—a necessary step in domains like finance or healthcare—they often inadvertently create the problem of 'keyterm overexpression.' As demonstrated, if a keyterm 'police' is supplied, and the user says 'policy,' the STT service, rather than failing or accepting the most likely word, may erroneously insert the intended keyterm, degrading the transcript's fidelity. The Keyterm Filtering API directly addresses this architectural flaw. It is not an STT service itself; rather, it is a highly specific, crucial gatekeeper. Its function is to analyze an audio stream and perform a phonetic verification check against a registered list of keyterms. Instead of merely accepting the provided keywords, it only returns the subset that can be phonetically *proven* to be present in the audio. This moves the developer workflow from merely *suggesting* words to *validating* spoken words. For the developer building a mission-critical conversational AI application, this level of input sanitization is invaluable. By passing only the phonetically-verified set of keywords to a downstream service like Deepgram, the developer effectively eliminates a major class of hallucinations related to forced keyterm insertion. The API is designed with clear endpoints (`POST/keyterms/register`, `POST/keyterms/filter`) and supports multiple input modalities (WAV, MP3 file uploads, or raw PCM data), ensuring it integrates cleanly into complex, real-time audio pipelines, including those utilizing AudioWorklet. While the API's functionality is highly specialized and valuable, users must remember its role: it filters, it does not transcribe. The entire process remains a multi-step workflow: Register $ ightarrow$ Filter $ ightarrow$ Transcribe. This structure prevents the API from solving all transcription problems, but its focused approach to input validation makes it an essential component for achieving enterprise-grade reliability in voice-based applications. For businesses relying on absolute transcription accuracy, this API is less of a feature and more of a necessary architectural safeguard.