Discover the versatility of speech recognition in various practical scenarios. Learn how this technology can be utilized to read text messages aloud in-car, provide closed captions for videos, automate public address systems, and transcribe telephone calls and meetings, enhancing communication and accessibility.
Table of Contents
Question
In which two scenarios can you use speech recognition? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. an in-car system that reads text messages aloud
B. providing closed captions for recorded or live videos
C. creating an automated public address system for a train station
D. creating a transcript of a telephone call or meeting
Answer
B. providing closed captions for recorded or live videos
D. creating a transcript of a telephone call or meeting
Explanation
The correct answers are B. providing closed captions for recorded or live videos and D. creating a transcript of a telephone call or meeting.
Speech recognition is a type of natural language processing that can convert speech to text or text to speech. Speech recognition can use advanced algorithms to analyze the sound, frequency, pitch, or context of the speech and return a text output or a speech output.
Two of the scenarios that can use speech recognition are:
- Providing closed captions for recorded or live videos: Speech recognition can be used to provide subtitles or captions for videos that contain speech, such as movies, TV shows, or online courses. Speech recognition can use techniques such as speech-to-text, speech translation, or speech synthesis to convert the speech in the video to text, translate the text to another language, or generate a speech output in another language.
- Creating a transcript of a telephone call or meeting: Speech recognition can be used to create a written record of a conversation that occurs over the phone or in a meeting, such as a customer service call, a sales call, or a team meeting. Speech recognition can use techniques such as speech-to-text, speaker identification, or speech synthesis to convert the speech in the conversation to text, identify the speakers, or generate a speech output from the text.
The other two scenarios are not suitable for using speech recognition, but for using other natural language processing services:
- An in-car system that reads text messages aloud: This is not a speech recognition scenario, but a text-to-speech scenario. Text-to-speech is a technique that can convert text to speech, such as reading text messages, emails, or web pages aloud. Text-to-speech can use techniques such as natural language understanding, natural language generation, or speech synthesis to process and understand text and generate a speech output.
- Creating an automated public address system for a train station: This is not a speech recognition scenario, but a speech synthesis scenario. Speech synthesis is a technique that can generate speech from text, such as announcing train arrivals, departures, or delays. Speech synthesis can use techniques such as natural language understanding, natural language generation, or speech synthesis to process and understand text and generate a speech output.
Reference
Microsoft Azure Products> Cognitive Services> Speech-to-Text > Overview
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