Mel-frequency cepstrum
PulseAugur coverage of Mel-frequency cepstrum — every cluster mentioning Mel-frequency cepstrum across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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Quantum Vision Theory Boosts Deepfake Speech Detection Accuracy
Researchers have introduced Quantum Vision (QV) theory, a novel approach inspired by quantum physics' particle-wave duality, for enhancing deepfake speech detection. This theory posits that data can exist as information…
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Wavelet techniques and SVM improve bird song classification accuracy
Researchers have developed a new framework for identifying and classifying invasive bird species vocalizations in noisy natural environments. The system utilizes Bayesian wavelet shrinkage with an Epanechnikov kernel fo…
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New framework enhances multimodal emotion recognition using attention-based fusion
Researchers have developed a new framework for multimodal emotion recognition, integrating audio and visual data. The audio component uses Wav2Vec2, MFCCs, and acoustic descriptors processed by a BiLSTM, while the video…
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New MADS descriptor set enhances audio analysis beyond spectral summaries
Researchers have developed MADS (Multi-view Acoustic Descriptor Set), a new 19-dimensional descriptor set designed to capture richer physical dynamics in audio signals beyond traditional spectral summaries. MADS encodes…
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New parameter-free method evaluates few-shot learning for elephant vocalizations
Researchers have developed a parameter-free method for evaluating few-shot learning in elephant vocalization classification. This approach uses nearest-centroid classification on fixed acoustic embeddings, comparing its…
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Audio foundation models capture phylogenetic signal without domain-specific training
A new study published on arXiv investigates whether large audio foundation models can capture phylogenetic signals from species vocalizations without explicit training for this purpose. The research found that general-p…
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Browser-native AI classifies electric guitar strings with 97% accuracy
Researchers have developed Fretiq, a novel system for classifying electric guitar strings directly within a web browser. This system utilizes a 26-dimensional feature representation, incorporating Mel-Frequency Cepstral…
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AI detects Alzheimer's from speech using acoustic features
Researchers have developed a lightweight method for detecting Alzheimer's disease using only spontaneous speech audio. This approach avoids the need for transcripts or computationally intensive deep learning models, ins…
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Wav2Vec 2.0 model interpretability for pathological speech assessment studied
Researchers have investigated the interpretability of a Wav2Vec 2.0 model used for assessing pathological speech in oral and oropharyngeal cancer patients. Using canonical correlation analysis, they measured the correla…
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New AI models tackle Chinese dialect discrimination using speech and transfer learning · 4 sources tracked
Two new research papers propose advanced methods for distinguishing between Chinese dialects, a task traditionally challenging due to limited text data. One paper introduces a speech-driven approach using Mel Frequency …
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New Paper Outlines Embedded ML Workflow for Microcontrollers
A new paper details a comprehensive workflow for implementing machine learning on microcontrollers, focusing on the engineering challenges of resource-constrained devices. It covers data acquisition, signal preprocessin…
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New research tackles spoofed speech detection with advanced AI models
Researchers are developing advanced methods to detect spoofed speech, a growing challenge due to realistic synthesis and voice conversion technologies. One approach, the Temporal Pyramid Adapter, uses parallel temporal …
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CNN achieves 91.79% accuracy for Hindi keyword spotting in speech recognition
Researchers have developed a keyword spotting system for Hindi speech recognition using a Convolutional Neural Network (CNN). The system was trained on 40,000 audio samples and utilizes Mel Frequency Cepstral Coefficien…