## 6 Conclusions  
By using an objective intelligibility metric (BiDWGP) as a perceptual guide, an approach is proposed to automate the selection of speech-to-background ratio in broadcast audio scenes. When a desired mixing level is predefined for a scene, this method is able to automatically validate whether a minimal intelligibility requirement is satisfied. It can also estimate the lowest mixing level (\(\text{SBR}_{min}\)) needed to meet the intelligibility requirement. In addition, an optimal SBR can be estimated by applying an extra gain to the estimated \(\text{SBR}_{min}\), to get a mix that not only maintains speech intelligibility but also considers other aspects of listener preference such as auditory comfort. Three perceptual listening experiments were conducted. In Expt. I, we investigated the target objective intelligibility score, which resulted from the minimum SBR level that listeners require to fully understand the speech content in a given background masker. When using each model prediction to estimate \(\text{SBR}_{min}\), the chosen BiDWGP metric yields the smallest errors compared to four state-of-the-art OIMs. In Expt. II, listener-preferred SBR levels for mixing in five different audio scenes were measured. This showed that a gain needs to be applied to the model-predicted \(\text{SBR}_{min}\) to get the preferred SBR. In the presence of noise, music, other sound effects or their combinations a gain of 5.5 dB is needed. When the background introduces informational masking (e.g., competing speech) a significantly larger gain of 23 dB may be required to alleviate the listening effort and the frequency of attention switching. However, further study is required to quantify the relationship between the additional gain and the degree of those factors affecting a listener's preference for competing speech. Expt. III was conducted to finally evaluate listening experiences in the audio scenes created using different mixing levels, including three constant and three scene-specific SBRs. The subjects ratings suggest that the SBR based on BiDWGP prediction with an additional gain derived from the measured listener-preferred SBRs in Expt. II, can provide the same good balance between speech intelligibility and background sound effects as the measured do, for the audio scenes tested in this study. Despite the optimal SBRs being acquired from fitting to the measured values, the ratings from different listeners--who were not involved in the measurement of the listener-preferred SBRs--confirmed the validity of the system-suggested SBRs. For automatic decision making, automatic sound tagging could be a solution to identify the background sound. The system can then apply appropriate additional gains to the scene. In critical situations, such as live broadcasts, voice-over-IP, and adaptive systems for the hearing-impaired listeners, such a system could maintain high levels of speech intelligibility and listening comfort, improving the listening experience. Further study may extend the proposed system by suggesting the optimal SBRs with respect to other factors, such as room acoustics and ambient noise in the listening environment, which may also degrade speech intelligibility. This work was supported by the EPSRC Programme Grant S3A: Future Spatial Audio for an Immersive Listener Experience at Home (EP/L000539/1) and the BBC as part of the BBC Audio Research Partnership. The authors would like to thank [PERSON] for conducting the listening experiments and for useful discussions. The experimental data underlying the findings are fully available without restriction, details are available from [[https://dx.doi.org/10.17866/rd.salford.5598082](https://dx.doi.org/10.17866/rd.salford.5598082)]([https://dx.doi.org/10.17866/rd.salford.5598082](https://dx.doi.org/10.17866/rd.salford.5598082)). Due to copyright restrictions, the radio drama material used in the listening experiments is not available from this link. [PERSON] designed all the experiments and composed the manuscript.