32
The difficulty with using older recordings to study performances is that it is virtually impossible to know everything that has gone into the recording chain, from the original performance to the wave form that is being analysed. There are three aspects of the recording chain that need to be considered in this project; the original recording, the repeated transcription processes and the final digitisation of the recordings.
There is little that can be identified with exactitude in the original recording process. The room, the microphone, the recording engineer and even the recording media are almost certainly unknown.33 However, what is known about early recording practices can allow a certain degree of certitude in the analysis that is being undertaken. There are a number of ways that early recordings are distorted, but that are unlikely to impact on this study. Even though electrical recording dramatically improved frequency response, the range that could be captured was still under 15kHz and nothing below 60Hz (Leech-Wilkinson 2009a, 3.1 para 29). However, those limits are far enough outside the frequencies that are used in this analysis of the female voice to be of little or no concern. The dynamic range of the recordings has probably been compressed, reducing loud sounds and amplifying soft sounds. However, as vocal loudness is not a part of the analysis, again this can be disregarded.
With a modern mixing desk, the mixer/engineer is able to change the frequency
response of the singer’s microphone very precisely and continuously throughout a song. However, the recordings in this study pre-date graphic equalisers and the most a mixer could do to a singer in the 30s-50s was to turn the mid-range up and down, relative to the treble and the bass. This is an incredibly coarse adjustment, comparable to adjusting a movie by turning the red, green or blue up or down—it does not change what is on— screen, nor does it change how many different colours are there. It just puts a very obvious cast over the whole thing.
If a recording has been copied and re-copied many times over the years, it may have been compressed a little and/or lost some frequency response each time. In addition, any digitally remastered recordings will have been cleaned up in some way, and it is not possible to know what might have been done. In order to minimise potential
distortions, caused by multiple transcriptions and remastering, as many original
33 There are a number of exceptions in this dissertation, such as radio and television transcriptions, and
recordings were sourced as possible and all sound recordings were treated the same way, using the same equipment and software. All 78rpm discs were flat transferred34 to digital format at Artsound FM (Canberra, Australia) and the Jazz Museum Bix Eiben Hamburg, while other analogue recordings were flat transferred using Audacity ® digital audio editor; no post transfer processing was undertaken. All audio files were converted to Waveform Audio File Format (WAV) using Wavepad Sound Editor Masters Edition v5.06, which is distributed by NCH Software. In order to maintain maximum audio quality, the files were saved in PCM uncompressed WAV format at 44100 Hz samples per second and 16 bits per sample35. The WAV files were then analysed using the VoceVista 3 voice analysis software for Windows36.
All final analysis was completed using a Dell Inspiron 1010 with an Intel ® Atom Processor, CPU Z530 @ 1.6 GHz, 1.00GB RAM, with integrated sound and graphics cards (Intel(R) High Definition Audio HDMI, Realtek High Definition Audio, Intel® HD Graphics Family and NVIDIA GeForce GT 525M) with no special modifications, running Windows 7. After discovering an unexplainable graphic incompatibility between this computer and Voce Vista, all graphic examples were created using a Toshiba Satellite Notebook Intel® Core ™ i7-4700MQ CPU @ 2.40GHz, 8.00GB RAM; with integrated sound and graphic cards (Intel® Display Audio, Realtek High Definition Audio, Intel® HD Graphics 4600 and NVIDIA GeForce GT 740M), running Windows 8.1. Where necessary, for clarity of labelling, the resulting spectrograms and power spectrums were edited using Microsoft Paint.37
The in-depth analysis of Martin’s vocal style rests on three vocal measures: tessitura with its concomitant point tessitura, vibrato, and the spectral analysis of her voice. These three analytical measures, used separately by researchers for many years to describe the voice and its use in various settings, are able to provide a multilayered, quantifiable measurement of the voice and this study aims to bring all three of these
34 In this study “flat transfer” refers to a digitization process with no post-transfer processing with the
possible exception of anti-click or noise reduction software (Timmers 2007a, 2873.
35
The Nyquist Sampling Theorem states that a sample waveform contains all the information, without distortions, when the sampling rate exceeds twice the highest frequency contained by the sampled waveform, a sampling rate of 44,100 Hz is sufficient to reproduce up to 20,000 Hz with no loss of fidelity. None of the examples used in this study require this level of bandwidth and focus on levels under 5000 Hz.
36 Available online at http://www.vocevista.com.
37 Bitmaps were cropped to isolate particular sections and clarifying text and symbols were inserted. The
together to form an in-depth picture of the voice of an individual performer. This study does not claim the depth of analysis that vocal science scholars are able to bring to this discussion, but offers a hybrid quantitative methodology intended to bridge the gap between their approaches and those of traditional musicology.