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| [ | |
| { | |
| "question": "When was the concept of Speech Recognition first introduced?", | |
| "options": [ | |
| "1920s", | |
| "1940s", | |
| "1960s", | |
| "1980s" | |
| ], | |
| "answer": "1960s" | |
| }, | |
| { | |
| "question": "What is Speech Recognition?", | |
| "options": [ | |
| "The ability to understand and interpret spoken language by computers", | |
| "The ability to recognize different accents and dialects", | |
| "The ability to convert written text into spoken words", | |
| "The ability to analyze the rhythm and intonation of speech" | |
| ], | |
| "answer": "The ability to understand and interpret spoken language by computers" | |
| }, | |
| { | |
| "question": "What are some common use cases of Speech Recognition technology?", | |
| "options": [ | |
| "Voice assistants", | |
| "Transcription services", | |
| "Call center automation", | |
| "All of the above" | |
| ], | |
| "answer": "All of the above" | |
| }, | |
| { | |
| "question": "What is the purpose of OpenAI's Whisper?", | |
| "options": [ | |
| "To improve automatic speech recognition systems", | |
| "To develop natural language processing algorithms", | |
| "To create voice synthesis models", | |
| "To enhance text-to-speech capabilities" | |
| ], | |
| "answer": "To improve automatic speech recognition systems" | |
| }, | |
| { | |
| "question": "Which programming language is commonly used in developing Speech Recognition applications?", | |
| "options": [ | |
| "Python", | |
| "Java", | |
| "C++", | |
| "JavaScript" | |
| ], | |
| "answer": "Python" | |
| }, | |
| { | |
| "question": "What are the challenges faced by Speech Recognition systems?", | |
| "options": [ | |
| "Background noise", | |
| "Accents and dialects", | |
| "Speech disorders", | |
| "All of the above" | |
| ], | |
| "answer": "All of the above" | |
| }, | |
| { | |
| "question": "What is the difference between automatic and interactive Speech Recognition?", | |
| "options": [ | |
| "Automatic Speech Recognition requires pre-recorded speech, while interactive Speech Recognition can process real-time speech", | |
| "Automatic Speech Recognition focuses on recognizing individual words, while interactive Speech Recognition understands the context of the speech", | |
| "Automatic Speech Recognition is used in voice assistants, while interactive Speech Recognition is used in transcription services", | |
| "There is no difference between automatic and interactive Speech Recognition" | |
| ], | |
| "answer": "Automatic Speech Recognition requires pre-recorded speech, while interactive Speech Recognition can process real-time speech" | |
| }, | |
| { | |
| "question": "Which company developed the first practical speech recognition system?", | |
| "options": [ | |
| "IBM", | |
| "Microsoft", | |
| "Apple", | |
| "Google" | |
| ], | |
| "answer": "IBM" | |
| }, | |
| { | |
| "question": "What is the primary technology behind modern Speech Recognition systems?", | |
| "options": [ | |
| "Hidden Markov Models (HMMs)", | |
| "Recurrent Neural Networks (RNNs)", | |
| "Support Vector Machines (SVMs)", | |
| "Convolutional Neural Networks (CNNs)" | |
| ], | |
| "answer": "Recurrent Neural Networks (RNNs)" | |
| }, | |
| { | |
| "question": "What is the role of language models in Speech Recognition?", | |
| "options": [ | |
| "To convert spoken words into written text", | |
| "To analyze the sentiment of the speech", | |
| "To improve the accuracy and context understanding of Speech Recognition systems", | |
| "To identify specific speech patterns and accents" | |
| ], | |
| "answer": "To improve the accuracy and context understanding of Speech Recognition systems" | |
| } | |
| ] |