Essays about: "audio data"
Showing result 1 - 5 of 304 essays containing the words audio data.
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1. Where to Fuse
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis investigates fusion techniques in multimodal transformer models, focusing on enhancing the capabilities of large language models in understanding not just text, but also other modalities like images, audio, and sensor data. The study compares late fusion (concatenating modality tokens after separate encoding) and early fusion (concatenating before encoding) techniques, examining their respective advantages and disadvantages. READ MORE
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2. A Comparative Analysis of Whisper and VoxRex on Swedish Speech Data
University essay from Uppsala universitet/Statistiska institutionenAbstract : With the constant development of more advanced speech recognition models, the need to determine which models are better in specific areas and for specific purposes becomes increasingly crucial. Even more so for low-resource languages such as Swedish, dependent on the progress of models for the large international languages. READ MORE
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3. Audio Anomaly Detection in Cars
University essay from Göteborgs universitet/Institutionen för matematiska vetenskaperAbstract : Audio anomaly detection in the context of car driving is a crucial task for ensuring vehicle safety and identifying potential faults. This paper aims to investigate and compare different methods for unsupervised audio anomaly detection using a data set consisting of recorded audio data from fault injections and normal "no fault" driving. READ MORE
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4. Navigating the Risks of Dark Data : An Investigation into Personal Safety
University essay from Linnéuniversitetet/Institutionen för informatik (IK)Abstract : With the exponential proliferation of data, there has been a surge in data generation fromdiverse sources, including social media platforms, websites, mobile devices, and sensors.However, not all data is readily visible or accessible to the public, leading to the emergence ofthe concept known as "dark data. READ MORE
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5. Gender Bias in Machine Learning : The Effect of Using Female Versus Male Audio When Classifying Emotions in Speech Using Machine Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : To avoid discrimination between the genders and to improve the performance of machine learning, it is important to evaluate how different test data can impact how accurate machine learning models can be. This study investigates if the distribution between women and men in the training data affects how accurately different machine learning models can classify emotions used in the speaker’s tone of voice. READ MORE