Download Signal Conversation

Please give me the option of transferring my full set of preserved conversation from one device to another device if I want to. I've just needed to reinstall Linux (Fedora 33) from scratch on my laptop (Thanks UEFI, BTW) - and all I got after doing "snap install signal-desktop" is a blank screen with this message - and no way to restore the previous state of conversations.

Clicking is one of the most robust metaphors for social connection. But how do we know when two people "click"? We asked pairs of friends and strangers to talk with each other and rate their felt connection. For both friends and strangers, speed in response was a robust predictor of feeling connected. Conversations with faster response times felt more connected than conversations with slower response times, and within conversations, connected moments had faster response times than less-connected moments. This effect was determined primarily by partner responsivity: People felt more connected to the degree that their partner responded quickly to them rather than by how quickly they responded to their partner. The temporal scale of these effects (

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In the first stage, Analyze, the complete conversation layout is determined when relevant speech is detected in the front hemisphere. The analysis includes localization of the talkers involved in the conversation and assessment of the conversation dynamics. In the second stage, Augment, advanced binaural processing is used to create three independent focus streams, which are added to the existing focus stream from the split processing, allowing talkers in the conversation to be enhanced, while background noise is processed independently as a surrounding stream. In the third stage, Adapt, the streams are combined to create a conversation sphere that changes adaptively according to changes in the conversation layout, e.g., when conversation partners take turns speaking, when they move or when the wearer turns their head.

Jensen et al. (2023) presented data from a study performed at Hrzentrum Oldenberg in Germany where the performance of Signia IX with RTCE was investigated using different implementations of a standardized speech-in-noise test. In tests simulating both a one-on-one conversation and a more challenging group conversation with multiple talkers, the study results showed significant benefits in speech understanding of Signia IX with RTCE activated compared to a setting in which RTCE was turned off. In a test simulating a group conversation scenario, 95% of the participants showed improved speech-in-noise performance with RTCE.

A clinically relevant question is, how does RTCE with its multi-stream architecture perform compared to other hearing aids with single stream processing? Specifically, we wanted to answer this question: What is the signal-to-noise ratio (SNR) benefit of Signia IX in a group conversation scenario compared to the benefit of products from competitors? The improvement in SNR is important because it is an essential prerequisite for speech understanding improvements in noisy situations. By using advanced measurement techniques, the processed SNR can be assessed at the output of the hearing aid, and accordingly, the differences between hearing aid processing approaches can be evaluated under well-controlled conditions.

In the following, we report on a benchtop investigation, in which Signia IX was compared to four different competitor products. The primary purpose of the investigation was to assess SNR differences across hearing aids in a simulated group conversation in background noise. First, we explain our measurement methods, and then we present and discuss our results.

There are some requirements which need to be fulfilled for this technique to work. Since it is based on a series of consecutive recordings, it is important that the hearing aids work in exactly the same way for all recordings. This means that the hearing aids are in the same stable working condition before each recording is started, and that they are subjected to the exact same stimuli in all recordings. In practice, the hearing aids should be exposed to a controlled (stable) input sound for as long as it takes to activate relevant features and reach a stable processing state before the recording is started. The Hagerman technique also requires that the hearing aid processing does not change the phase of the signal, since this would eliminate the effect of the phase inversion. Since some special features like automatic feedback cancellation and frequency compression typically involve some (unpredictable) changes of the phase, such features need to be turned off.

Figure 2. Setup used for output SNR measurements. Speech (S) signals were presented from the two loudspeakers in the front hemisphere, and noise (N) signals were presented from the two loudspeakers in the back hemisphere. The signals processed by the hearing aids were recorded in the KEMAR ears, with and without phase inversion of each signal, and the Hagerman method was used to generate estimates of the various S and N signals, both alone and in combination.

To determine the output SNR, the hearing aids were positioned in the KEMAR ears, and a series of recordings were made with and without phase inversion of the different input signals. Applying the phase-inversion technique on the recordings then allowed estimation of each of the processed signals at the output of the hearing aids, both for the individual speech and noise sources, and for the combined speech and noise, as illustrated in Figure 2.

In the measurements, the sound signals from the four loudspeakers were presented as shown in Figure 3. The figure shows how signals from all four loudspeakers were presented for 50 seconds before the actual recordings were started. This 50-second time lag, as mentioned above, ensures all noise reduction features are activated and stable before the phase-inversion technique is applied. The time required to settle varied across the hearing aids, and the value of 50 seconds was determined by the fact that one of the hearing aids required just above 40 seconds to reach a stable condition in this setup. At t=50 seconds the recording was started, and the presentation scheme changed to simulate a group conversation with two talkers taking turns speaking. This was established by alternating between S0 and S315, with each signal being presented for 10 seconds as indicated in Figure 3. Each recording included two sections with S0 and two sections with S315, for a total of 40 seconds.

Figure 3. Presentation of input signals from the four loudspeakers. The signal presentation started at t=0, while recordings used for the analysis were started at t=50 seconds to allow enough time for the hearing aids to reach a stable working condition (i.e., the same condition for each hearing aid in each recording). The analysis was based on 40 seconds of recordings (evaluation time), including two sections of 10 seconds from each of the two talker locations (S0 and S315). This setup simulates the turn-taking of two talkers in the frontal hemisphere of the wearer with continuous noise originating from the rear/lateral hemisphere.

The outcome of the analysis is the output SNR of the different hearing aids, averaged across the evaluation time. Due to the test layout where speech was presented from the front and from the left side of the KEMAR, we present the output SNRs of the left hearing aid, which is most relevant to speech understanding due to the better ear effect. In the analysis, we calculated the overall conversation SNR, (S0+S315)/(N135+N225), based on the entire 40 seconds recording.

Among the four hearing aids offering a benefit compared to the unaided KEMAR, Signia IX clearly offered the largest benefit. The overall output SNR of Signia IX was 11.8 dB, while the best competitor device (Brand B) offered an output SNR of 7.7 dB. That is, in this conversation scenario, Signia IX offered an improvement in output SNR of 4.1 dB compared to the nearest competitor. Compared to the open KEMAR ear, Signia IX improved the overall conversation SNR by almost 8 dB.

Regarding the differences between the hearing aids, even though some changes in the ranking of the hearing aids appear when looking at the frontal and lateral SNRs, respectively, the overall trends in Figure 5 generally follow the trend in the overall conversation SNR shown in Figure 4 For example, it is clear that Brand C had problems for both talker directions, which show SNR values around 5 dB poorer than the open ear KEMAR values.

Importantly, for both the frontal and lateral output SNRs, Figure 5 shows a very clear Signia IX advantage compared to the competitor devices. For Signia IX, an output SNR of 9.9 dB was measured for the frontal talker, which was 3.8 dB higher than the best competitor (Brand A), and 8.9 dB higher than the open-ear SNR. For the lateral talker, Signia IX offered an output SNR of 13.3 dB, which was 3.6 dB higher than the best competitor (Brand D) and 7.5 dB higher than the open-ear SNR. These findings suggest that Signia IX and RTCE offers a substantial benefit when listening to all the participants in a conversation, independent of their position relative to the wearer.

In this study, we investigated the output SNR performance of Signia IX and four competitor devices in a simulated group conversation scenario with two conversation partners in the front hemisphere and with continuous noise coming from the back hemisphere. The results showed Signia IX outperformed all four competitors, offering an overall conversation SNR benefit of 4.1 dB (compared to the nearest competitor) and benefits of at least 3.6 dB for specific talker directions.

We believe that this pronounced difference between Signia IX and the premium devices of four competitors stems from the RTCE processing. One unique element of RTCE is the advanced analysis of the conversation layout, which continuously pinpoints conversation partners as well as the location of noise sources. In the given measurement setup, the system always knows whether speech is coming from the front or the side direction. This allows another unique element of RTCE, the multi-stream architecture with its three focus streams (which are added to the focus stream of the split processing), to tailor the processing of each stream according to the conversation layout, thereby creating a live auditory space where active talkers are enhanced, and other surrounding extraneous sounds are processed independently. By updating the system 1,000 times per second, RTCE adapts to any changes in the conversation layout, including the turn-taking between participants in the conversation. The test setup in our investigation simulated this turn-taking by presenting speech alternating from the front and the side of the KEMAR manikin. 006ab0faaa