The short-time Fourier transform (STFT) based spectrogram is commonly used to analyze the time-frequency content of a signal. By the choice of window length, the STFT provide a trade-off between time and frequency resolutions. This paper presents a novel method that achieves high resolution simultaneously in both time and frequency. We extend Probabilistic Latent Component Analysis (PLCA) to jointly decompose two spectrograms, one with a high time resolution and one with a high frequency resolution. Using this decomposition, a new spectrogram, maintaining high resolution in both time and frequency, is constructed. Termed the ``super-resolution spectrogram", it can be particularly useful for speech as it can simultaneously resolve both glottal pulses and individual harmonics.
Bibliographic reference. Nam, Juhan / Mysore, Gautham J. / Ganseman, Joachim / Lee, Kyogu / Abel, Jonathan S. (2010): "A super-resolution spectrogram using coupled PLCA", In INTERSPEECH-2010, 1696-1699.