Prosodic Event Recognition using Convolutional Neural Networks with Context Information
This paper demonstrates the potential of convolutional neural networks (CNN) for detecting and classifying prosodic events on words, specifically pitch accents and phrase boundary tones, from frame-based acoustic features. Typical approaches use not only feature representations of the word in question but also its surrounding context. We show that adding position features indicating the current word benefits the CNN. In addition, this paper discusses the generalization from a speaker-dependent modelling approach to a speaker-independent setup. The proposed method is simple and efficient and yields strong results not only in speaker-dependent but also speaker-independent cases.
Code (0)
등록된 구현이 없습니다.
Tasks
PositionSimilar Papers 제목 키워드 기반
Voice Quality and Pitch Features in Transformer-Based Speech Recognition
Jitter and shimmer measurements have shown to be carriers of voice quality and prosodic information which enhance the performance of tasks like speaker recognition, diarization or automatic speech recognition (ASR). Howe…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Speaker Recognitionspeech-recognition+1Non-verbal information in spontaneous speech -- towards a new framework of analysis
Non-verbal signals in speech are encoded by prosody and carry information that ranges from conversation action to attitude and emotion. Despite its importance, the principles that govern prosodic structure are not yet ad…
speech-recognitionSpeech RecognitionVowelPrompt: Hearing Speech Emotions from Text via Vowel-level Prosodic Augmentation
Emotion recognition in speech presents a complex multimodal challenge, requiring comprehension of both linguistic content and vocal expressivity, particularly prosodic features such as fundamental frequency, intensity, a…
Reinforcement LearningEmotion RecognitionImproving coreference resolution with automatically predicted prosodic information
Adding manually annotated prosodic information, specifically pitch accents and phrasing, to the typical text-based feature set for coreference resolution has previously been shown to have a positive effect on German data…
coreference-resolutionCoreference ResolutionImproving Mandarin Prosodic Structure Prediction with Multi-level Contextual Information
For text-to-speech (TTS) synthesis, prosodic structure prediction (PSP) plays an important role in producing natural and intelligible speech. Although inter-utterance linguistic information can influence the speech inter…
DecoderMulti-Task Learningtext-to-speechText to Speech