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Spatial sound reasoning is a fundamental human skill, enabling us to navigate and interpret our surroundings based on sound. In this paper we present BAT, which combines the spatial sound perception ability of a binaural acoustic scene analysis model with the natural language reasoning capabilities of a large language model (LLM) to replicate this innate ability. To address the lack of existing datasets of in-the-wild spatial sounds, we synthesized a binaural audio dataset using AudioSet and SoundSpaces 2.0. Next, we developed SpatialSoundQA, a spatial sound-based question-answering dataset, offering a range of QA tasks that train BAT in various aspects of spatial sound perception and reasoning. The acoustic front end encoder of BAT is a novel spatial audio encoder named Spatial Audio Spectrogram Transformer, or Spatial-AST, which by itself achieves strong performance across sound event detection, spatial localization, and distance estimation. By integrating Spatial-AST with LLaMA-2 7B model, BAT transcends standard Sound Event Localization and Detection (SELD) tasks, enabling the model to reason about the relationships between the sounds in its environment. Our experiments demonstrate BAT's superior performance on both spatial sound perception and reasoning, showcasing the immense potential of LLMs in navigating and interpreting complex spatial audio environments. 

SUMMARY Global variations in the propagation of fundamental-mode and overtone surface waves provide unique constraints on the low-frequency source properties and structure of the Earth’s upper mantle, transition zone and mid mantle. We construct a reference data set of multimode dispersion measurements by reconciling large and diverse catalogues of Love-wave (49.65 million) and Rayleigh-wave dispersion (177.66 million) from eight groups worldwide. The reference data set summarizes measurements of dispersion of fundamental-mode surface waves and up to six overtone branches from 44 871 earthquakes recorded on 12 222 globally distributed seismographic stations. Dispersion curves are specified at a set of reference periods between 25 and 250 s to determine propagation-phase anomalies with respect to a reference Earth model. Our procedures for reconciling data sets include: (1) controlling quality and salvaging missing metadata; (2) identifying discrepant measurements and reasons for discrepancies; (3) equalizing geographic coverage by constructing summary rays for travel-time observations and (4) constructing phase velocity maps at various wavelengths with combination of data types to evaluate inter-dataset consistency. We retrieved missing station and earthquake metadata in several legacy compilations and codified scalable formats to facilitate reproducibility, easy storage and fast input/output on high-performance-computing systems. Outliers can be attributed to cycle skipping, station polarity issues or overtone interference at specific epicentral distances. By assessing inter-dataset consistency across similar paths, we empirically quantified uncertainties in traveltime measurements. More than 95 per cent measurements of fundamental-mode dispersion are internally consistent, but agreement deteriorates for overtones especially branches 5 and 6. Systematic discrepancies between raw phase anomalies from various techniques can be attributed to discrepant theoretical approximations, reference Earth models and processing schemes. Phase-velocity variations yielded by the inversion of the summary data set are highly correlated (R ≥ 0.8) with those from the quality-controlled contributing data sets. Long-wavelength variations in fundamental-mode dispersion (50–100 s) are largely independent of the measurement technique with high correlations extending up to degree ∼25. Agreement degrades with increasing branch number and period; highly correlated structure is found only up to degree ∼10 at longer periods (T > 150 s) and up to degree ∼8 for overtones. Only 2ζ azimuthal variations in phase velocity of fundamental-mode Rayleigh waves were required by the reference data set; maps of 2ζ azimuthal variations are highly consistent between catalogues ( R = 0.6–0.8). Reference data with uncertainties are useful for improving existing measurement techniques, validating models of interior structure, calculating teleseismic data corrections in local or multiscale investigations and developing a 3-D reference Earth model. 

Abstract This report is on the synthesis by electrospinning of multiferroic core-shell nanofibers of strontium hexaferrite and lead zirconate titanate or barium titanate and studies on magneto-electric (ME) coupling. Fibers with well-defined core–shell structures showed the order parameters in agreement with values for nanostructures. The strength of ME coupling measured by the magnetic field-induced polarization showed the fractional change in the remnant polarization as high as 21%. The ME voltage coefficient in H-assembled films showed the strong ME response for the zero magnetic bias field. Follow-up studies and potential avenues for enhancing the strength of ME coupling in the core–shell nanofibers are discussed.