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Update assets/quiz.json

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  1. assets/quiz.json +60 -60
assets/quiz.json CHANGED
@@ -1,102 +1,102 @@
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  [
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  {
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- "question": "Which of the following best describes speech recognition?",
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  "options": [
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- "Teaching computers to understand human speech",
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- "Teaching humans to understand computer languages",
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- "Teaching computers to write code",
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- "Teaching humans to speak multiple languages"
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  ],
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- "answer": "Teaching computers to understand human speech"
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  },
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  {
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- "question": "What is one of the popular applications of speech recognition?",
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  "options": [
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- "Facial recognition",
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- "Virtual reality gaming",
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- "Voice assistants",
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- "Emotion detection"
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  ],
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- "answer": "Voice assistants"
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  },
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  {
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- "question": "Which decade saw the introduction of Hidden Markov Models (HMMs) in speech recognition?",
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  "options": [
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- "1960s",
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- "1970s",
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- "1980s",
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- "1990s"
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  ],
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- "answer": "1980s"
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  },
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  {
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- "question": "What was the purpose of the DARPA challenges in speech recognition?",
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  "options": [
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- "To promote research and advancements in the field",
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- "To train voice assistants",
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- "To improve internet connectivity",
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- "To develop social media platforms"
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  ],
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- "answer": "To promote research and advancements in the field"
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  },
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  {
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- "question": "What role did neural networks play in speech recognition?",
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  "options": [
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- "They helped in translating spoken language",
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- "They allowed for automatic extraction of features from speech data",
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- "They facilitated handwriting recognition",
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- "They improved internet security"
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  ],
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- "answer": "They allowed for automatic extraction of features from speech data"
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  },
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  {
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- "question": "Which popular voice assistant was introduced in 2011?",
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  "options": [
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- "Siri",
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- "Alexa",
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- "Cortana",
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- "Google Assistant"
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  ],
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- "answer": "Siri"
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  },
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  {
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- "question": "What recent advancements have contributed to the improvement of speech recognition?",
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  "options": [
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- "Neural networks and deep learning",
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- "Augmented reality technology",
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- "Quantum computing",
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- "Robotics"
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  ],
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- "answer": "Neural networks and deep learning"
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  },
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  {
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- "question": "In which field is speech recognition commonly used to convert spoken words into written text?",
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  "options": [
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- "Medical diagnosis",
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- "Automotive engineering",
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- "Transcription services",
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- "Space exploration"
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  ],
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- "answer": "Transcription services"
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  },
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  {
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- "question": "How does speech recognition technology benefit individuals with disabilities?",
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  "options": [
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- "It helps improve memory and cognitive skills",
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- "It enables them to interact with technology through voice commands",
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- "It provides physical therapy",
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- "It helps improve vision and hearing abilities"
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  ],
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- "answer": "It enables them to interact with technology through voice commands"
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  },
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  {
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- "question": "Which speech recognition system developed by OpenAI is known for its state-of-the-art performance?",
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  "options": [
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- "Whisper",
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- "Roomba",
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- "Siri",
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- "Echo"
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  ],
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- "answer": "Whisper"
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  }
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  ]
 
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  [
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  {
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+ "question": "When was the concept of Speech Recognition first introduced?",
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  "options": [
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+ "1920s",
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+ "1940s",
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+ "1960s",
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+ "1980s"
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  ],
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+ "answer": "1960s"
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  },
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  {
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+ "question": "What is Speech Recognition?",
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  "options": [
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+ "The ability to understand and interpret spoken language by computers",
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+ "The ability to recognize different accents and dialects",
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+ "The ability to convert written text into spoken words",
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+ "The ability to analyze the rhythm and intonation of speech"
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  ],
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+ "answer": "The ability to understand and interpret spoken language by computers"
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  },
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  {
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+ "question": "What are some common use cases of Speech Recognition technology?",
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  "options": [
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+ "Voice assistants",
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+ "Transcription services",
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+ "Call center automation",
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+ "All of the above"
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  ],
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+ "answer": "All of the above"
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  },
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  {
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+ "question": "What is the purpose of OpenAI's Whisper?",
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  "options": [
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+ "To improve automatic speech recognition systems",
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+ "To develop natural language processing algorithms",
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+ "To create voice synthesis models",
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+ "To enhance text-to-speech capabilities"
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  ],
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+ "answer": "To improve automatic speech recognition systems"
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  },
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  {
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+ "question": "Which programming language is commonly used in developing Speech Recognition applications?",
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  "options": [
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+ "Python",
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+ "Java",
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+ "C++",
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+ "JavaScript"
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  ],
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+ "answer": "Python"
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  },
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  {
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+ "question": "What are the challenges faced by Speech Recognition systems?",
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  "options": [
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+ "Background noise",
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+ "Accents and dialects",
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+ "Speech disorders",
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+ "All of the above"
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  ],
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+ "answer": "All of the above"
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  },
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  {
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+ "question": "What is the difference between automatic and interactive Speech Recognition?",
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  "options": [
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+ "Automatic Speech Recognition requires pre-recorded speech, while interactive Speech Recognition can process real-time speech",
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+ "Automatic Speech Recognition focuses on recognizing individual words, while interactive Speech Recognition understands the context of the speech",
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+ "Automatic Speech Recognition is used in voice assistants, while interactive Speech Recognition is used in transcription services",
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+ "There is no difference between automatic and interactive Speech Recognition"
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  ],
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+ "answer": "Automatic Speech Recognition requires pre-recorded speech, while interactive Speech Recognition can process real-time speech"
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  },
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  {
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+ "question": "Which company developed the first practical speech recognition system?",
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  "options": [
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+ "IBM",
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+ "Microsoft",
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+ "Apple",
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+ "Google"
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  ],
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+ "answer": "IBM"
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  },
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  {
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+ "question": "What is the primary technology behind modern Speech Recognition systems?",
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  "options": [
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+ "Hidden Markov Models (HMMs)",
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+ "Recurrent Neural Networks (RNNs)",
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+ "Support Vector Machines (SVMs)",
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+ "Convolutional Neural Networks (CNNs)"
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  ],
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+ "answer": "Recurrent Neural Networks (RNNs)"
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  },
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  {
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+ "question": "What is the role of language models in Speech Recognition?",
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  "options": [
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+ "To convert spoken words into written text",
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+ "To analyze the sentiment of the speech",
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+ "To improve the accuracy and context understanding of Speech Recognition systems",
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+ "To identify specific speech patterns and accents"
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  ],
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+ "answer": "To improve the accuracy and context understanding of Speech Recognition systems"
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  }
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  ]