# Enhancing Interactive Communication with the OVBOX: New Features and Applications in Hearing Research

Giso Grimm, Volker Hohmann

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Giso Grimm, Volker Hohmann. Enhancing Interactive Communication with the OVBOX: New Features and Applications in Hearing Research. Proceedings of the 19th Linux Audio Conference, Jun 2025, Lyon, France. hal-05096038

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<figure><img src="image_1.png" /></figure>
# ENHANCING INTERACTIVE COMMUNICATION WITH THE OVBOX: NEW FEATURES AND APPLICATIONS IN HEARING RESEARCH

Giso Grimm *

Auditory Signal Processing
and Cluster of Excellence “Hearing4all”
Department of Medical Physics and Acoustics
Carl von Ossietzky Universität Oldenburg, Germany
g.grimm@uol.de

Volker Hohmann

Auditory Signal Processing
and Cluster of Excellence “Hearing4all”
Department of Medical Physics and Acoustics
Carl von Ossietzky Universität Oldenburg, Germany
volker.hohmann@uol.de

## ABSTRACT

The OVBOX system provides low-latency, real-time transmission of audio and multi-modal data, facilitating interactive communication in a variety of applications. This paper presents new features, including data encryption, and demonstrates the capabilities of the OVBOX system through three exemplary applications. The first application involves streaming a live concert from four different locations, demonstrating the system's ability to handle complex, geographically distributed audio transmissions. The second application presents a hearing research study investigating the impact of head movement on communication success, highlighting the system's utility in scientific investigations. The third application explores the feasibility of conducting EEG hyperscanning studies using the OVBOX system, illustrating its potential for advancing neuroscience research. Our findings provide insights into the design of effective interactive communication systems and highlight the potential of the OVBOX system to advance our understanding of human communication and perception.

## 1. INTRODUCTION

With energy costs rising and borders closing, the importance of low-latency acoustic telepresence tools for music and voice communication cannot be underestimated. Telepresence technology allows people to communicate over the internet. This is usually achieved using established videoconferencing tools such as Zoom, Facetime, Jitsi or many of the other tools that received a lot of attention during the COVID19 pandemic. When it comes to music and research applications, a limiting factor of video-conferencing tools is the delay between the sender and receiver (end-to-end delay), as well as the use of noise reduction, echo cancellation and sound gating, which prevent natural turn taking in speech conversation and rhythmic musical interaction.

In face-to-face communication, the delay between sender and receiver is limited only by the speed of sound and the distance between them. It typically reaches values between 3 ms, corresponding to a distance of 1 m in a typical speech conversation, and 30 ms, corresponding to a distance of 10 m, which can occur between musicians on stage. For acoustic music, this is also the upper limit for unhindered rhythmic interaction [1]. The transition time of turns in speech communication is typically in the order of 300 ms [2], which is much less than the latency of speech production. This means that in interactive communication the prediction of turn takes is crucial. This requires low end-to-end delays as well as the transmission of the cues necessary for prediction [2, 3].

Telepresence systems typically rely on an Internet connection that is shared with many other users and applications. Given the uncontrollable nature of Internet delays, minimising latency at both the sender and receiver ends is critical. This has led to a number of telepresence tools that specialise in delay minimisation. An overview of existing solutions for music applications

can be found in [4]. Solutions with the shortest latencies often run on dedicated hardware running the Linux operating system [5, 6, 7]. Low-latency audio transmission for acoustic interaction is conceptionally different from distributed recording systems (e.g. WAM-studio, [8]) or telematic music systems based on event triggers or pre-scored (e.g., L2ORK tweeter, [9]), just to mention a few examples from the Internet of sounds literature [10]. Such systems are therefore not further discussed in this paper.

The aim of this paper is to report on extensions to the open source tool OVBOX [11, 7], which was first presented at LAC2020. The OVBOX was developed to enable rhythmic interaction of music with acoustic sources using the Internet. In this paper we describe the extension to support low-latency transmission of user-provided UDP data and timestamps for post-hoc transmission time correction, and the extension to support end-to-end encryption of audio and user data. Both of these extensions are essential for hearing research applications. Therefore, in addition to these extensions, we highlight three example applications: a concert streamed live from different locations, and two applications in the fields of hearing research and neuroscience.

## 2. OVERVIEW OF THE OVBOX SYSTEM

In response to the increased need for remote music collaboration tools during the COVID-19 pandemic, we developed the OVBOX system [7, 12], a system designed for low-latency network audio communication. The OVBOX system overcomes the limitations of existing tools such as Zoom and Jamulus by achieving end-to-end delays below 30 ms for distances up to approximately 1500 km (see [7] for a detailed delay and jitter analysis of different network technologies), making it suitable for low-latency communication applications in music and research.

The system architecture comprises client devices, a configuration server and session servers, using a client-server model for remote configuration and traversal of network address translation barriers, see Figure 1 for an overview. The client software, implemented in C++, integrates a Representational State Transfer Application Programming Interface (REST API) client, a User Datagram Protocol (UDP) forwarding tool, a network audio client [13], and the TASCAR acoustic simulation engine for 3D spatial audio rendering [14, 15]. This setup allows for individualised audio mixing and spatial rendering, which is particularly beneficial for musicians playing instruments with similar timbres.

Optimised for headless operation on a Raspberry Pi 4B, pre-configured images for the OVBOX client are offered to ensure low-latency audio processing, a feature that is difficult to achieve on typical desktop systems. However, desktop client packages are available for Ubuntu Linux, Archlinux, MacOS and, on an experimental basis, Microsoft Windows. The system supports both Selective Forwarding Unit (SFU) and Peer-to-peer (P2P) network topologies. Jitter compensation is user adjustable to balance low-latency and packet loss.

<footnote>* Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 352015383 - SFB 1330 B1</footnote>
<figure><img src="image_2.png" /><figcaption>Figure 1: *Server structure of the OVBOX system. The OVBOX devices request their configuration from the configuration server, and the session servers advertise their services to the configuration server (green lines). When a device joins a session, it establishes a session management connection with the session server and exchanges its IP address, port number, operating mode and public encryption key (blue lines). Finally, all devices within a session can exchange audio and other user data via encrypted UDP messages (red line).*</figcaption></figure>

Performance evaluations show that the OVBOX system achieves high computational efficiency. In a comparison including a Mac Mini (M1), Linux Desktop (i5), Raspberry Pi 3B+ and 4B, the Mac Mini was leading in CPU usage, followed closely by a Linux desktop and Raspberry Pi 4B. The Raspberry Pi 3B+ shows limitations with smaller block sizes, highlighting the importance of hardware selection.

<table><caption>Table 1: *CPU usage and self-monitoring round trip time in a session with four peers. Data from [7].*</caption><thead><tr><th rowspan="2">Hardware</th><th colspan="2">2 ms block size</th><th colspan="2">1 ms block size</th></tr><tr><th>CPU %</th><th>RTT ms</th><th>CPU %</th><th>RTT ms</th></tr></thead><tbody><tr><td>Raspberry Pi 3B+</td><td>62</td><td>9.25</td><td>n.a.</td><td>5.4</td></tr><tr><td>Raspberry Pi 4B</td><td>24</td><td>9.13</td><td>34</td><td>5.13</td></tr><tr><td>Linux i5-8500 (5.15.0-97-lowlatency)</td><td>8.2</td><td>6.04</td><td>15</td><td>3.9</td></tr><tr><td>mac mini M1 2020 (monterey 12.7.3)</td><td>4.6</td><td>9.04</td><td>5.7</td><td>7.04</td></tr></tbody></table>

The end-to-end delay between two peers, which can typically be achieved over distances of up to 1500 km using fibre optics or DSL technology with default settings, is in the range of 30 to 50 ms. For example, 30 ms end-to-end delay has been reported for connections between Pristina (Kosovo) and Oldenburg (Germany) and between Rome (Italy) and Kiel (Germany), and 40 ms for connections between Paris (France) and Oldenburg (Germany) as well as Budapest (Hungary) and Oldenburg (Germany). A detailed analysis of delays as well as an open data set can be found in [7].

## 2.1. Data Routing, Message Handling and Session Management

The core of the OVBOX is a data router that packs and forwards UDP packets from the local network to the other peers, either directly from peer to peer or via the session server, depending on the operating mode. A packet consists of a header containing a session-wide secret code, the sender identification, the destination port number and a packet counter. The rest of the packet is the original data packet. When a message is received on the external port, the header is decoded. If the session code matches, the packet is sorted to reduce the number of out-of-order messages and finally forwarded to the appropriate local port.

Data packets with reserved special port numbers are used for special purposes, such as measuring round trip time and communicating with the session server. Each client signals its presence to the session server by sending periodic registration messages. The session server shares the IP address, external port number and operating mode with all devices participating in the same session. Devices are considered to be offline if no registration or data message has been received for several seconds.

## 2.2. Audio Transmission

The open source tool 'zita-njbridge' [13] is used for network encoding and decoding of audio as well as jitter buffer handling. On the sender side the OVBOX client software launches an instance of 'zita-j2n' with as many channels as the device should send. The destination port number depends on the session ID of the device, which is unique within a session. For each remote client participating in the same session, an instance of 'zita-n2j' is started, listening on the port number assigned to the remote session ID.

## 2.3. User Data Transmission

User data can be forwarded to all remote devices of the session in the same way as audio data is transmitted, since the data router is completely agnostic of the packet content. The only difference is that the forwarded port needs to be configured explicitly (using the configuration web interface). This way any unicast UDP-based data, e.g., OSC messages, can be shared within a session with little effort.

In neuroscience research, the Lab Streaming Layer (LSL) is commonly used to exchange EEG signals, trigger events or other biophysical sensor data [16]. This protocol uses a mixture of multicast and unicast UDP messages, which cannot be routed directly through the OVBOX system. To enable the transmission of LSL data streams and events, a bidirectional converter between LSL and OSC was developed and added to the system. Although not all the metadata embedded in LSL data streams can be transferred in this way, it is possible to exchange LSL data within an OVBOX session.

Two special ports are allocated by the OVBOX process: UDP port 9871 is used to receive OSC messages, which control features of the local acoustic simulation tool, including any extensions (see section 2.5 for details). Data sent to UDP port 9870 will be forwarded to port 9871 of all other peers, but will not be processed locally.

## 2.4. Encryption

The OVBOX system uses libsodium [17], a modern and efficient cryptographic library, to implement data encryption using key pair encryption. This method uses asymmetric cryptography, where a public key is used for encryption and a corresponding private key for decryption, to ensure secure data transmission. The session server plays a key role in managing the exchange of public keys between clients, facilitating the establishment of secure communication channels without prior contact between the parties. Encrypted data is sent to all devices for which a public key is available. The encryption status is displayed in the user interface on the configuration server.

By using encryption, each data package is increased in size by 32 Bytes. This results in an increase of overall data usage of approximately 22%; for a measurement see Table 2. Despite the added security, the system maintains minimal data and computational overhead, ensuring efficient operation even on resource-constrained devices such as the Raspberry Pi single-board computer. This balance of security and performance is critical for real-time applications where both data integrity and low latency are essential. By using libsodium's optimised algorithms, the
OVBOX system achieves seamless and secure communication without breaking compatibility with previous versions.

<table><caption>Table 2: Data usage of an OVBOX device in a session with three participants. All parameters except encryption and operating mode were left at their default settings.</caption><thead><tr><td>Encryption</td><td>Operating mode</td><td>Upstream MBit/s</td><td>Downstream MBit/s</td></tr></thead><tbody><tr><td>off</td><td>peer-to-peer</td><td>1.78</td><td>1.78</td></tr><tr><td>off</td><td>server</td><td>0.9</td><td>1.78</td></tr><tr><td>on</td><td>peer-to-peer</td><td>2.17</td><td>2.17</td></tr><tr><td>on</td><td>server</td><td>1.09</td><td>2.17</td></tr></tbody></table>

## 2.5. Extending the OVBOX Functionality

The underlying acoustic simulation tool, TASCAR, provides laboratory management tools that go far beyond acoustic simulation, e.g. data logging, sensor integration and OSC interfaces that allow almost any feature to be controlled in real time. This allows most of the features of TASCAR to be used in the OVBOX. In addition to the generic acoustic scene controlled by the OVBOX system, it is possible to add any TASCAR configuration written in XML code.

### 2.5.1. Example: Controlling DMX Lamps remotely

For example, it is possible to add a USB based DMX controller and control the connected 3 channel DMX controllable RGB fixtures with the following additional TASCAR code, entered via the configuration web interface:

```xml
<?xml version="1.0"?>
<session>
  <modules>
    <lightctl driver="opendmxusb"
              device="/dev/ttyUSB0">
      <lightscene name="scene"
                  channels="3">
        <layout>
          < fixture addr="15"
                    label="lamp1"/>
          < fixture addr="30"
                    label="lamp2"/>
        </layout>
      </lightscene>
    </lightctl>
  </modules>
</session>
```

To control 'lamp1' to fade to green from any other client, the RGB or HSV values and a fade time can be sent via OSC:

```
send_osc osc.udp://192.168.0.50:9870/
    /light/scene/lamp1/fade 0 255 0 1
send_osc osc.udp://192.168.0.50:9870/
    /light/scene/lamp1/hsv 120 1 1 1
```

Here we assume that the remote OVBOX client device has the IP address 192.168.0.50; if the desktop client is used, the OSC messages can be sent locally. Similarly, most other TASCAR modules can be integrated by adding the appropriate configuration. All plugins are documented in the TASCAR documentation [18].

### 2.5.2. Example: Sending Time Stamps and LSL Streams

To send time stamps from two devices to a central data logging, we assume a setup with three devices. One of the device is a desktop client running on the same computer as the data logging. On the first device, enter this additional TASCAR code:

```xml
<?xml version="1.0"?>
<session>
  <modules>
    <lsl2osc streams="EEG"
              prefix="/lab1"/>
    <system path="/cal"
              seepath="/lab1/time"
              sendsessiontime="true"/>
    <oscrelay startwith="/lab1"
              url="osc.udp://localhost:9870/"/>
  </modules>
</session>
```

On the second device, the same code can be used but with 'lab1' replaced by 'lab2'. On the data logging client (desktop GUI client), this configuration is required to record data in Matlab format:

```xml
<?xml version="1.0"?>
<session>
  <modules>
    <datalogging outputdir="${HOME}">
      <osc path="/lab1/EEG" size="33"/>
      <osc path="/lab2/EEG" size="33"/>
      <osc path="/lab1/time" size="2"/>
      <osc path="/lab2/time" size="2"/>
    </datalogging>
  </modules>
</session>
```

We assume that a 32 channel EEG LSL stream is available on the subnet of OVBOX 1 and 2; the LSL time stamp is additionally sent in the first channel, thus resulting in a total of 33 channels. The time line of the sending devices can be controlled via OSC on the data logging computer:

```
send_osc 9870 /transport/locate 0
send_osc 9870 /transport/start
```

The timestamps now include the remote session time and the system clock in seconds since midnight. A screenshot of the data logging window is shown in Figure 2.

<figure><img src="image_3.png" /><figcaption>Figure 2: Screenshot of the data logging window during EEG stream and timestamp recording, with one device active and one inactive. The time line of the sending device was started at approximately second 25.</figcaption></figure>
# 3. EXAMPLE APPLICATIONS

## 3.1. Streaming Concert played live from different Locations

The OVBOX system is actively used by many ensembles and individuals for online rehearsals, teaching, streaming concerts or international master classes [19]. In this section we describe the setup used for a concert for five viola da gamba, played live from four different locations [20], see Figure 3 for a screenshot.

During the pandemic, concerts were put on hold due to lockdowns, leaving both musicians and audiences unable to gather. To bridge this gap, streaming concerts became a popular alternative. In one such concert, five musicians from different locations in northern Germany (Hamburg, Bremen, Oldenburg and Ottersberg) connected via the internet to perform together. The musicians’ locations were connected using a variety of technologies, ranging from direct Ethernet connections to fibre optics and DSL. For two of the locations, the audio was routed through a central server in Frankfurt/Main to optimise the use of the bandwidth required for the low quality internet connection.

At one of the sites, the audio was not only used for live performance, but also remixed with a physical model of a concert hall using TASCAR [14]. This mixed audio was then streamed live on YouTube, allowing a wider audience to experience the concert in real time. To provide a visual experience as well as the audio, videos of each musician were streamed to the streaming location using jitsi [21]. A background video with a dome projection was rendered using the Blender game engine [22] and mixed with the musician videos and the stereo mix of the audio using OBS Studio [23], streamed as a video stream in 1440p resolution. In the youtube studio the stream was configured as a 360 degree interactive video. Unfortunately, ambisonics audio is not supported in Youtube live streams, so only a stereo mix was used, regardless of the current viewing angle. The musicians did not see any video.

In the OVBOX system, a second instance of zita-n2j was started for each musician, with a larger jitter compensation buffer size, set to 50 ms instead of 10 ms, for the broadcast audio stream, as a slight additional delay in the streamed audio is not critical (compared to the audio for direct musical interaction). An additional audio delay of 400 ms was added in the mix to achieve a rough temporal alignment of the jitsi videos with the audio signal.

<figure><img src="image_4.png" /><figcaption>Figure 3: Screenshot of a streaming concert for five viola da gamba, played live from four different locations [20].</figcaption></figure>

## 3.2. Evaluation of Hearing Aids in Interactive Conversation

We have used the OVBOX system for several applications in hearing aid and communication research to achieve telepresence in virtual reality [24, 25, 26]. Participants were placed in a virtual reality lab with a 300-degree cylindrical projection screen and a 45-channel spherical loudspeaker array. The confederates

were in separate rooms in the same building and wore headphones with a headset microphone. The focus was on the transmission of multiple modalities along with the audio, such as head movements and gaze behaviour. A schematic overview of this setup is shown in Figure 4.

<figure><img src="image_5.png" /><figcaption>Figure 4: Overview of the setup to measure the effect of head movements on conversation success. The test participant is seated in a virtual reality lab with a 300 degree field-of-view video projection within a 45-channel spherical loudspeaker array (top left part of the figure). The two confederates were located in different rooms (bottom right part of the figure). Their audio signal and head movement data was transmitted to the laboratory using the OVBOX system. Depending on the measurement condition, different methods of avatar control were used.</figcaption></figure>

One of the studies based on the OVBOX system investigated how avatar head movement animation affects immersion and conversational success in virtual environments [25]. The aim is to improve evaluation methods for assistive listening technology, in particular to develop evaluation paradigms in which test subjects display conversation-specific gaze and head movement behaviour. Key to such paradigms is the evaluation of hearing aids in interactive conversations. The use of telepresence and avatar representation of interlocutors can disentangle the underlying factors of conversational behaviour.

Participants engaged in triadic conversations with two confederates in a simulated virtual pub environment, with their interlocutors represented by avatars. Four levels of avatar animation realism were tested: static heads, automatic head movements controlled by onsets in the audio signal, transferred head movements, and transferred video. In this study, the OVBOX system was used to transmit audio and head movement data, see Figures 4 and 5 for an overview. The head motion data was captured using an open hardware head tracker based on an MPU6050 motion processor connected to an ESP8266 WiFi microcontroller. The head movement data was used locally to control the orientation of the virtual receiver, resulting in an interactive binaural rendering of the virtual acoustic scene. Simultaneously, the head movement data was transmitted to the avatar representations presented to the participant and to a central data logging system. The experiment was controlled by OSC messages sent from a node.js web server. In this way, the entire experiment was controlled by one of the confederates via a web interface.

The results show that when representing the interlocutors with avatars, the animation level of the head movements has a
<figure><img src="image_6.png" /><figcaption>Figure 5: Example image of a test participant in the lab (top panel), and the two confederates connected via OVBOX systems (bottom panel).</figcaption></figure>

significant effect on the participant's speech behaviour as well as head movement behaviour, but also influences the success of the conversation (for details see [27]).

### 3.3. EEG Hyperscanning

This paper presents an innovative application of the OVBOX system, extending its capabilities to include EEG hyperscanning for real-time, low-latency transmission over the Internet [28]. EEG hyperscanning involves the simultaneous recording of brain activity from multiple people in order to study interpersonal neural synchronisation during social interactions. The OVBOX, originally designed for low-latency audio transmission, has been adapted to transmit EEG data, motion sensors and audio signals, enabling telepresence scenarios for research in social neuroscience and beyond.

The study demonstrates the real-time transmission of EEG data alongside audio and motion data. It also proves that low-latency transmission is possible: The system achieves minimal delay and jitter, which is critical for synchronising data from geographically separated participants, ensuring accurate analysis of interpersonal neural interactions. In the study, feasibility of using the OVBOX in a variety of tasks is shown: The paper presents results from four experimental conditions – response to tone, hand clapping, forced turn-taking, and free conversation-demonstrating the system's versatility and effectiveness in capturing synchronised neural activity and communication behaviour.

The system enables researchers to study brain activity during real-time interactions, providing insights into interpersonal synchrony and communication dynamics. The integration of EEG hyperscanning into a low-latency audio system opens new avenues for the study of musical interactions and ensemble performance. The capabilities of the system suggest applications in virtual environments, enhancing immersive experiences and enabling new forms of remote collaboration and interaction.

<figure><img src="image_7.png" /><figcaption>Figure 6: Overview of the setup for EEG hyperscanning. The two participants were located in two different labs, the data were recorded in a third lab. Next to the audio signals, EEG data and clock signals were transmitted, to allow an exact measurement of the end-to-end delays.</figcaption></figure>

## 4. CONCLUSIONS

The OVBOX system is designed for low-latency interactive communication over the Internet. The two main applications are in music, to enable distributed rehearsals and hybrid concert formats, and in hearing and communication research, to transmit audio and behavioural data in real time. Key features are both flexibility and robust data security. The effectiveness of the OVBOX system is demonstrated by three example studies presented here. The incorporation of end-to-end encryption for both audio and user data resulted in a marginal increase in data usage with no significant impact on computational performance.

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[15] Giso Grimm, “Tascar toolbox for acoustic scene creation and rendering,” https://tascar.org/, 2025.

[16] Christian Kothe, Seyed Yahya Shirazi, Tristan Stenner, David Medine, Chadwick Boulay, Matthew I. Grivich, Tim Mullen, Arnaud Delorme, and Scott Makeig, “The Lab Streaming Layer for synchronized multimodal recording,” Feb. 2024.

[17] Frank Denis, “libsodium,” https://github.com/jedisct1/libsodium.

[18] Giso Grimm, Joanna Luberadzka, Fenja Schwark, Tobias Herzke, and Volker Hohmann, *TASCAR user manual*, Carl von Ossietzky Universität Oldenburg, 2025, https://github.com/gisogrimm/tascar/wiki/master/manual.pdf.

[19] Netzwerk 4.0 der Musikhochschulen, “barock:connect - hochschulübergreifender digitaler Meisterkurs Barockvioline,” https://www.youtube.com/watch?v=U2Bdn_KpTps, 2024.

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[23] Lain Bailey, “OBS studio,” https://obsproject.com/, 2012.

[24] Marie Hartwig, Volker Hohmann, and Giso Grimm, “Speaking with avatars - influence of social interaction on movement behavior in interactive hearing experiments,” 2021, pp. 94–98.

[25] Giso Grimm, Angelika Kothe, and Volker Hohmann, “Effect of head motion animation on immersion and conversational benefit in turn-taking conversations via telepresence in audiovisual virtual environments,” in *Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023*. Jan. 2023, FA2023, European Acoustics Association.

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[28] Giso Grimm, Mareike Daeglau, Volker Hohmann, and Stefan Debener, “EEG hyperscanning in the internet of sounds:low-delay real-time multi-modal transmissionusing the OVBOX,” in *2024 IEEE 5th International Symposium on the Internet of Sounds (IS2)*. Sept. 2024, pp. 1–8, IEEE.