Crowdsourcing a Reverberation Descriptor Map

Abstract

Audio production is central to every kind of media that involves sound, such as film, television, and music and involves transforming audio into a state ready for consumption by the public. One of the most commonly-used audio production tools is the reverberator. Current interfaces are often complex and hard-to-understand. We seek to simplify these interfaces by letting users communicate their audio production objective with descriptive language (e.g. "Make the drums sound bigger."). To achieve this goal, a system must be able to tell whether the stated goal is appropriate for the selected tool (e.g. making the violin warmer using a panning tool does not make sense). If the goal is appropriate for the tool, it must know what actions lead to the goal. Further, the tool should not impose a vocabulary on users, but rather understand the vocabulary users prefer. In this work, we describe SocialReverb, a project to crowdsource a vocabulary of audio descriptors that can be mapped onto concrete actions using a parametric reverberator. We deployed SocialReverb, on Mechanical Turk, where 513 unique users described 256 instances of reverberation using 2861 unique words. We used this data to build a concept map showing which words are popular descriptors, which ones map consistently to specific reverberation types, and which ones are synonyms. This promises to enable future interfaces that let the user communicate their production needs using natural language.

Audealize: Crowdsourced Audio Production Tools

“…Mo et al [14] found that emotional cues can be conveyed via reverberation. Some of their emotional categories, such as romantic and mysterious, overlap with the vocabulary found in our data collection [4]. Their work is a vocabulary study, like our prior work [4], whereas our current work uses a vocabulary to build and test an interface.…”

“…Since our approach depends on crowdsourced collection of mappings between words and effects control settings. We now provide a brief overview of the SocialReverb [4] and SocialEQ [5] user interactions for data collection. For further detail, please refer to the prior publications.…”

“…SocialReverb is a project to crowdsource a vocabulary of audio descriptors that can be mapped onto concrete actions using a parametric reverberator. We deployed Social-Reverb on Mechanical Turk where 513 unique users described 256 instances of reverberation using 2861 unique words, from which the 369 words that showed broadest agreement among participants [4] were selected for use in the current work.…”

“…When a word is selected, the sound is modified to embody the descriptive term. The interface vocabulary is seeded from a crowdsourced set of natural language descriptors collected in two previous studies [4] [5], rather than a curated list made by tool-builders or experts in audio (e.g. audiologists, recording engineers, developers of audio plugin software).…”

Perceptual Evaluation and Analysis of Reverberation in Multitrack Music Production

“…Very little work is available on novel, more intuitive interfaces for reverb [13,14] and mapping terms to its parameters [4,5]. A number of studies have looked at perception of reverberation in musical contexts [2,6,[15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32], see Table 1.…”