Even for people that do want transcription, though, often you can handily beat the accuracy of off-the-shelf services by tuning the models to the domain.
I'm pasting some copy from our website in part because I can't talk too much about specifics, but here's some examples:
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High quality speech to text transcription, including in the very difficult areas of conversational human-to-human speech: phone calls, voicemails, meetings, etc. Classification of speech & language: identifying gender, age, regional accents, level of education, etc. Voice front-ends for various applications and devices, including natural language interfaces: heads-up displays, robots, smartphone apps, etc. Speech synthesis (a.k.a. TTS) to generate high-quality synthesized speech from text. Analysis of audio: detecting different types of noise or speech: dog bark, shouting, gunshot, water running, cars, etc. Customization of speech recognition to processed signals, such as proprietary compression or noise reduction algorithms Fine-grained analysis of speech and language, for giving feedback in language pathology or language learning. Analysis of speech & language to detect various health conditions: stroke, dementia, depression, schizophrenia, etc. Information extraction from text or audio: phone numbers, dates, entities and relationships, etc. " [0]