Showing papers on "Spectrogram published in 1972"
TL;DR: In this article, a computer method was developed for obtaining information for spectrographic analysis from the output of an automatic microphotometer, where lines of analytical interest were located in the digitised spectrogram by a pattern recognition procedure.
Abstract: A computer method has been developed for obtaining information for spectrographic analysis from the output of an automatic microphotometer. The lines of analytical interest are located in the digitised spectrogram by a pattern recognition procedure. This procedure requires the use of a dis-persion equation, which is obtained automatically from a wavelength reference spectrum recorded on the plate. The method is applicable to spectrograms obtained from both grating and prism spectrographs.
4 citations
Patent•
15 Mar 1972
TL;DR: In this paper, a spectrogram display control unit that provides control of the displaying of frequency spectrum data in a composite X-Y display having multiple spectra data displayed in line by line arrangement, with the line spectrum data being updated and refreshed serially.
Abstract: A spectrogram display control unit that provides control of the displaying of frequency spectrum data in a composite X-Y display having multiple spectra data displayed in line by line arrangement, with the line spectra data being updated and refreshed serially. The spectra data is restored in a circulating memory shift register that receives updated information in timed sequence from another memory unit, which other memory unit provides time-controlled, interrogation of frequency data. The other memory unit can also average spectra data stored therein and supplied to the circulating memory unit at selected time intervals, that prevents loss of data between updating times.
3 citations
TL;DR: A simple user‐oriented computer language has been developed to be used as an aid in reading spectrograms of sentences containing words from a fixed vocabulary that provides insight into the kinds of acoustic analysis that are necessary in developing strategies for the machine recognition of connected speech.
Abstract: A simple user‐oriented computer language has been developed (using LISP) to be used as an aid in reading spectrograms of sentences containing words from a fixed vocabulary. The lexicon is stored in the computer in terms of phonetic segments and features. Questions such as “Give me all two‐word combinations that contain the following sequence of phonetic segments or features….” are easily translatable into simple and concise commands in this language. All commands are expressed in terms of phonetic segments or features which the user deduces from the spectrogram. In cases where segmentation is not obvious, a feature may be specified over a variable number of segments. It has been found that the use of such a language in conjunction with the reading of spectrograms provides insight into the kinds of acoustic analysis that are necessary in developing strategies for the machine recognition of connected speech. The language and some implications of its usage, based on experience with a 200‐word vocabulary, wil...
1 citations
[...]
TL;DR: In this article, a method for visual display of acoustical waveforms with which different phonemes are more readily distinguished than with spectrograms is presented. The visual display is based on the interval between successive up crossings of the zero axis in the waveform.
Abstract: This paper presents a method for visual display of acoustical waveforms with which different phonemes are more readily distinguished than with spectrograms. The visual display is based on the interval between successive up crossings of the zero axis in the waveform. Although zero crossings and tip crossings have been used by several investigators since Licklinder's studies demonstrating that zero‐crossing information is sufficient for intelligibility of speech, most investigators have ignored an essential property of up‐crossing analysis. Analysis of up crossings is a time domain technique and as such, allows a perfect resolution of events in time, a resolution which is lost if the up‐crossing data is averaged over intervals of time. Such precise time resolution is critical for the recognition of certain distinguishing features in various consonants. These features permit a visual display in which the phonemes can easily be distinguished, even in connected speech. Furthermore, the important features for d...
1 citations