alright, let's try once more.

paper/paper.md

@@ -53,24 +53,110 @@ for both sound generation and sonification, enabling users to efficiently apply
 Additionally, the toolbox includes educational Jupyter notebooks with illustrative code examples demonstrating the 
 application of sonification and visualization methods to deepen understanding within specific MIR scenarios.
 
+
+# Statement of Need
+Music data, characterized by attributes such as pitch, melody, harmony, rhythm, structure, and timbre, is inherently 
+intricate. Visualizations are crucial in deciphering this complexity by presenting music representations graphically,
+enabling researchers to identify patterns, trends, and relationships not immediately evident in raw data.
+For instance, visualizing time-dependent two-dimensional feature representations such as spectrograms (time--frequency),
+chromagrams (time--chroma), or tempograms (time--tempo) enhances comprehension of signal processing concepts 
+insights into the musical and acoustic properties of audio signals. Moreover, the combined visualization of extracted 
+features and reference annotations facilitates detailed examination of algorithmic approaches at a granular level. 
+These qualitative assessments, alongside quantitative metrics, are essential for comprehending the strengths, 
+weaknesses, and assumptions underlying music processing algorithms.
+The MIR community has developed numerous toolboxes, such as essentia [@BogdanovWGGHMRSZS13_essentia_ISMIR],
+madmom [@BoeckKSKW16_madmom_ACM-MM], Chroma Toolbox [@MuellerEwert11_ChromaToolbox_ISMIR], Tempogram Toolbox 
+[@GroscheM11_TempogramToolbox_ISMIR-lateBreaking], Sync Toolbox [@MuellerOKPD21_SyncToolbox_JOSS], Marsyas 
+[@Tzanetakis09_MARSYAS_ACM-MM], or the  MIRtoolbox [@LartillotT07_MirToolbox_ISMIR], offering modular code for music 
+signal processing and analysis, many of which also include data visualization methods.
+Notably, the two Python packages librosa [@McFeeRLEMBN15_librosa_Python] and libfmp [@MuellerZ21_libfmp_JOSS] aim to
+lower the barrier to entry for MIR research by providing accessible code alongside visualization functions,
+bridging the gap between education and research.
+
+As an alternative or addition to visualizing data, one can employ data sonification techniques to produce acoustic 
+feedback on extracted or annotated information [@KramerEtAl99SonificAR]. This is especially important in music,
+where humans excel at detecting even minor variations in the frequency and timing of sound events.
+For instance, people can readily perceive irregularities and subtle changes in rhythm when they listen to a pulse 
+track converted into a sequence of click sounds. This ability is particularly valuable for MIR tasks such as beat
+tracking and rhythm analysis. Moreover, transforming frequency trajectories into sound using sinusoidal models can 
+offer insights for tasks like estimating melody or separating singing voices. Furthermore, an auditory representation
+of a chromagram provides listeners with an understanding of the harmony-related tonal information contained in an 
+audio signal. Therefore, by converting data into sound, sonification can reveal subtle audible details in music 
+that may not be immediately apparent within visual representations.
+
+In the MIR context, sonification methods have been employed to provide deeper insights into various music annotations 
+and feature representations. For instance, the Python package librosa [@McFeeRLEMBN15_librosa_Python] offers a function 
+\texttt{librosa.clicks} that generates an audio signal with click sounds positioned at specified times, with options 
+to adjust the frequency and duration of the clicks. Additionally, the Python toolbox libf0 [@RosenzweigSM22_libf0_ISMIR-LBD] 
+provides a function (\texttt{libf0.utils.sonify\_trajectory\_with\_sinusoid}) for sonifying F0 trajectories using sinusoids.
+Moreover, the Python package libfmp~\citep{MuellerZ21_libfmp_JOSS} includes a function 
+(\texttt{libfmp.b.sonify\_chromagram\_with\_signal}) for sonifying time--chroma representations.
+Testing these methods, our experiments have revealed that current implementations frequently rely on inefficient
+event-based looping, resulting in excessively long runtimes. For instance, generating a click soundtrack for beat 
+annotations of 10-minute recordings can require \meinard{impractically long processing times}.
+
+In our Python toolbox, libsoni, we offer implementations of various sonification methods, including those 
+mentioned above. These implementations feature a coherent API and are based on straightforward methods that are 
+transparent and easy to understand. By utilizing efficient matrix-based implementations, the need for looping is 
+avoided, making them more efficient. Additionally, libsoni includes all essential components for sound synthesis, 
+operating as a standalone tool that can be easily extended and customized. The methods in libsoni enable
+interactivity, allowing for data manipulation and sonification, as well as the ability to alter feature 
+extraction or sonification techniques. While real-time capabilities are not currently included in libsoni,
+this could be a potential future extension. Hence, libsoni may not only be beneficial for MIR researchers but also for
+educators, students, composers, sound designers, and individuals exploring new musical concepts.
+
+
+## Chromagram Representations (libsoni.chroma)
+Humans perceive pitch in a periodic manner, meaning that pitches separated by an octave are perceived as having a 
+similar quality or acoustic color, known as chroma. This concept motivates the use of time--chroma representations 
+or chromagrams, where pitch bands that differ spectrally by one or several octaves are combined to form a single chroma
+band~\citep{MuellerEwert11_ChromaToolbox_ISMIR}. These representations capture tonal information related to harmony and 
+melody while exhibiting a high degree of invariance with respect to timbre and instrumentation. 
+Chromagrams are widely used in MIR research for various tasks, including chord recognition and structure analysis.
+The libsoni.chroma module provides sonification methods for chromagrams based on Shepard tones. 
+These tones are weighted combinations of sinusoids separated by octaves and serve as acoustic counterparts to 
+chroma values. The functions offered by libsoni enable the generation of various Shepard tone variants and can be 
+applied to symbolic representations (such as piano roll representations or chord annotations) or to chroma features 
+extracted from music recordings. This facilitates deeper insights for listeners into chord recognition results or the 
+harmony-related tonal information contained within an audio signal.
+
+
+## Spectrogram Representations (libsoni.spectrogram)
+Similar to chromagrams, pitch-based feature representations can be derived directly from music recordings using 
+transforms such as the constant-Q-transform (CQT), see\citep{SchoerkhuberK10_ConstantQTransform_SMC}. 
+These representations are a special type of log-frequency spectrograms, where the frequency axis is logarithmically 
+spaced to form a pitch-based axis. More generally, in audio signal processing, there exists a multitude of different
+time--frequency representations. For example, classic spectrograms have a linear frequency axis, usually computed via
+the short-time Fourier transform (STFT). Additionally, mel-frequency spectrograms utilize the mel scale, 
+which approximates the human auditory system's response to different frequencies. The Spectrogram module of libsoni
+is designed to sonify various types of spectrograms with frequency axes spaced according to linear, logarithmic,
+or mel scales. Essentially, each point on the scale corresponds to a specific center frequency,
+meaning that each row of the spectrogram represents the energy profile of a specific frequency over time. 
+Our sonification approach generates sinusoids for each center frequency value with time-varying amplitude values,
+in accordance with the provided energy profiles, and then superimposes all these sinusoids. Transforming
+spectrogram-like representations into an auditory experience, our sonification approach allows for a more 
+intuitive understanding of the frequency and energy characteristics within a given music recording.
+
+
 # Design Choices
 When designing the Python toolbox libsoni, we had several objectives in mind. Firstly, we aimed to maintain close 
-connections with existing sonification methods provided in in librosa[@McFeeRLEMBN15_librosa_Python] and 
-libfmp[@MuellerZ21_libfmp_JOSS]. Secondly, we re-implemented and included all necessary components 
+connections with existing sonification methods provided in in librosa [@McFeeRLEMBN15_librosa_Python] and 
+libfmp [@MuellerZ21_libfmp_JOSS]. Secondly, we re-implemented and included all necessary components 
 (e.g., sound generators based on sinusoidal models and click sounds), even though similar basic functionality is 
 available in other Python packages such as librosa and libfmp. By doing so, libsoni offers a coherent API along with 
 convenient but easily modifiable parameter presets. Additionally, the implementations are more efficient than previous 
-software. Thirdly, we adopted many design principles suggested by librosa[@McFeeRLEMBN15_librosa_Python]  
+software. Thirdly, we adopted many design principles suggested by librosa [@McFeeRLEMBN15_librosa_Python]  
 and detailed in [@McFeeKCSBB19_OpenSourcePractices_IEEE-SPM] to lower the entry barrier for students and 
 researchers who may not be coding experts. This includes maintaining an explicit and straightforward programming 
 style with a flat, functional hierarchy to facilitate ease of use and comprehension. The source code for
-libsoni, along with comprehensive API documentation, is publicly accessible through a dedicated GitHub
-repository [^3]. We showcase all components, including introductions to MIR scenarios, illustrations, and sound examples
+libsoni, along with comprehensive API documentation [^1], is publicly accessible through a dedicated GitHub
+repository [^2]. We showcase all components, including introductions to MIR scenarios, illustrations, and sound examples
 via Jupyter notebooks.  Finally, we have included the toolbox in the Python Package Index (PyPI), enabling
-installation with the standard Python package manager, pip [^4].
+installation with the standard Python package manager, pip [^3].
 
-[^3]: <https://github.com/groupmm/libsoni>
-[^4]: <https://groupmm.github.io/libsoni>
+[^1]: <https://groupmm.github.io/libsoni>
+[^2]: <https://github.com/groupmm/libsoni>
+[^3]: <https://pypi.org/project/libsoni>
 
 # Acknowledgements
 The libsoni package originated from collaboration with various individuals over the past years. We extend our gratitude 

paper/references.bib

@@ -22,6 +22,16 @@ @article{McFeeKCSBB19_OpenSourcePractices_IEEE-SPM
   doi       = {10.1109/MSP.2018.2875349}
 }
 
+@inproceedings{BoeckKSKW16_madmom_ACM-MM,
+  author    = {Sebastian B{\"o}ck and Filip Korzeniowski and Jan Schl{\"u}ter and Florian Krebs and Gerhard Widmer},
+  title     = {madmom: {A} New {P}ython Audio and Music Signal Processing Library},
+  booktitle = {Proceedings of the {ACM} International Conference on Multimedia ({ACM-MM})},
+  address   = {Amsterdam, The Netherlands},
+  pages     = {1174--1178},
+  year      = {2016},
+  doi       = {10.1145/2964284.2973795}
+}
+
 @book{Mueller15_FMP_SPRINGER,
   author    = {Meinard M\"{u}ller},
   title     = {Fundamentals of Music Processing -- Audio, Analysis, Algorithms, Applications},
@@ -41,4 +51,63 @@ @inproceedings{McFeeRLEMBN15_librosa_Python
   address   = {Austin, Texas, USA},
   year      = {2015},
   doi       = {10.25080/Majora-7b98e3ed-003}
-}
+}
+
+@inproceedings{BogdanovWGGHMRSZS13_essentia_ISMIR,
+  author    = {Dmitry Bogdanov and Nicolas Wack and Emilia G{\'o}mez and Sankalp Gulati and Perfecto Herrera and Oscar Mayor and Gerard Roma and Justin Salamon and Jos{\'e} R. Zapata and Xavier Serra},
+  title     = {Essentia: An Audio Analysis Library for Music Information Retrieval},
+  booktitle = {Proceedings of the International Society for Music Information Retrieval Conference ({ISMIR})},
+  pages     = {493--498},
+  address   = {Curitiba, Brazil},
+  year      = {2013},
+  doi       = {10.5281/zenodo.1415016}
+}
+
+@inproceedings{MuellerEwert11_ChromaToolbox_ISMIR,
+  author     = {Meinard M{\"u}ller and Sebastian Ewert},
+  title      = {{C}hroma {T}oolbox: {MATLAB} implementations for extracting variants of chroma-based audio features},
+  booktitle  = {Proceedings of the International Society for Music Information Retrieval Conference ({ISMIR})},
+  address    = {Miami, Florida, USA},
+  year       = {2011},
+  pages      = {215--220},
+  url-pdf    = {2011_MuellerEwert_ChromaToolbox_ISMIR.pdf},
+  url-details = {https://www.audiolabs-erlangen.de/resources/MIR/chromatoolbox},
+  doi        = {10.5281/zenodo.1416032}
+}
+
+@inproceedings{GroscheM11_TempogramToolbox_ISMIR-lateBreaking,
+  author    = {Peter Grosche and Meinard M{\"u}ller},
+  title     = {{T}empogram {T}oolbox: {MATLAB} Tempo and Pulse Analysis of Music Recordings},
+  booktitle = {Demos and Late Breaking News of the International Society for Music Information Retrieval Conference ({ISMIR})},
+  address   = {Miami, Florida, USA},
+  year      = {2011},
+  url-pdf = {2011_GroscheMueller_TempogramToolbox_ISMIR-LateBreaking.pdf},
+  url-details = {https://www.audiolabs-erlangen.de/resources/MIR/tempogramtoolbox}
+}
+
+@inproceedings{Tzanetakis09_MARSYAS_ACM-MM,
+  author    = {George Tzanetakis},
+  title     = {Music analysis, retrieval and synthesis of audio signals {MARSYAS}},
+  booktitle = {Proceedings of the {ACM} International Conference on Multimedia ({ACM-MM})},
+  address   = {Vancouver, British Columbia, Canada},
+  pages     = {931--932},
+  year      = {2009},
+  doi       = {10.1145/1631272.1631459}
+}
+
+@inproceedings{LartillotT07_MirToolbox_ISMIR,
+  author    = {Olivier Lartillot and Petri Toiviainen},
+  title     = {{MIR} in {MATLAB} {(II):} {A} Toolbox for Musical Feature Extraction from Audio},
+  booktitle = {Proceedings of the International Society for Music Information Retrieval Conference ({ISMIR})},
+  address   = {Vienna, Austria},
+  year      = {2007},
+  pages     = {127--130},
+  doi       = {10.5281/zenodo.1417145}
+}
+
+@book{KramerEtAl99SonificAR,
+  title={Sonification Report: Status of the Field and Research Agenda},
+  author={Gregory Kramer and Bruce Walker and Terri Bonebright and Perry Cook and John H. Flowers and Nadine Miner and John Neuhoff},
+  year={1999},
+  publisher={International Community for Auditory Display}
+}