Artificial Intelligence (AI) and Machine Learning (ML) will hold the key place in the huge transformation of the Automotive Industry by integrating them into designing autonomous cars. Together with other areas like supply chain management, manufacturing operations, mobility services, image, and video analytics, audio analytics plays an important role to make self-driving cars a success. With the advanced technological developments and innovations, the automotive industry is reshaping and adopting new technologies. Audio analytics has drastically changed car companies' focus on their products to improve customer satisfaction. The global market size of autonomous cars will grow up to 60 billion USD by 2030.
Audio Analytics under Machine Learning in driverless cars consists of Audio classification, NLP, voice/speech, and sound recognition. Voice and speech recognition has become an integral part of the autonomous cars and automotive industry. In the previous models of cars, voice and speech recognition was a challenge because of the lack of efficient algorithms, reliable connectivity, and processing power at the edge. Also, in-car cabin noise reduced the performance of the audio analytics which resulted in false recognition.
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