Dynamic Acoustic Unit Augmentation With BPE-Dropout for Low-Resource End-to-End Speech Recognition

With the rapid development of speech assistants, adapting server-intended automatic speech recognition (ASR) solutions to a direct device has become crucial. Researchers and industry prefer to use end-to-end ASR systems for on-device speech recognition tasks. This is because end-to-end systems can be made resource-efficient while maintaining a higher quality compared to hybrid systems. However, building end-to-end models requires a significant amount of speech data. Another challenging task associated with speech assistants is personalization, which mainly lies in handling out-of-vocabulary (OOV) words. In this work, we consider building an effective end-to-end ASR system in low-resource setups with a high OOV rate, embodied in Babel Turkish and Babel Georgian tasks. To address the aforementioned problems, we propose a method of dynamic acoustic unit augmentation based on the BPE-dropout technique. It non-deterministically tokenizes utterances to extend the token's contexts and to regularize their distribution for the model's recognition of unseen words. It also reduces the need for optimal subword vocabulary size search. The technique provides a steady improvement in regular and personalized (OOV-oriented) speech recognition tasks (at least 6% relative WER and 25% relative F-score) at no additional computational cost. Owing to the use of BPE-dropout, our monolingual Turkish Conformer established a competitive result with 22.2% character error rate (CER) and 38.9% word error rate (WER), which is close to the best published multilingual system.Comment: 16 pages, 7 figure

Temperatures Near the Lunar Poles and Their Correlation With Hydrogen Predicted by LEND

The lunar polar regions offer permanently shadowed regions (PSRs) representing the only regions which are cold enough for water ice to accumulate on the surface. The Lunar Exploration Neutron Detector (LEND) aboard the Lunar Reconnaissance Orbiter (LRO) has mapped the polar regions for their hydrogen abundance which possibly resides there in the form of water ice. Neutron suppression regions (NSRs) are regions of excessive hydrogen concentrations and were previously identified using LEND data. At each pole, we applied thermal modeling to three NSRs and one unclassified region to evaluate the correlation between hydrogen concentrations and temperatures. Our thermal model delivers temperature estimates for the surface and for 29 layers in the sub‐surface down to 2 m depth. We compared our temperature maps at each layer to LEND neutron suppression maps to reveal the range of depths at which both maps correlate best. As anticipated, we find the three south polar NSRs which are coincident with PSRs in agreement with respective (near)‐surface temperatures that support the accumulation of water ice. Water ice is suspected to be present in the upper ≈19 cm layer of regolith. The three north polar NSRs however lie in non‐PSR areas and are counter‐intuitive as such that most surfaces reach temperatures that are too high for water ice to exist. However, we find that temperatures are cold enough in the shallow sub‐surface and suggest water ice to be present at depths down to ≈35–65 cm. Additionally we find ideal conditions for ice pumping into the sub‐surface at the north polar NSRs. The reported depths are observable by LEND and can, at least in part, explain the existence and shape of the observed hydrogen signal. Although we can substantiate the anticipated correlation between hydrogen abundance and temperature the converse argument cannot be made

Target-Speaker Voice Activity Detection: a Novel Approach for Multi-Speaker Diarization in a Dinner Party Scenario

Speaker diarization for real-life scenarios is an extremely challenging problem. Widely used clustering-based diarization approaches perform rather poorly in such conditions, mainly due to the limited ability to handle overlapping speech. We propose a novel Target-Speaker Voice Activity Detection (TS-VAD) approach, which directly predicts an activity of each speaker on each time frame. TS-VAD model takes conventional speech features (e.g., MFCC) along with i-vectors for each speaker as inputs. A set of binary classification output layers produces activities of each speaker. I-vectors can be estimated iteratively, starting with a strong clustering-based diarization. We also extend the TS-VAD approach to the multi-microphone case using a simple attention mechanism on top of hidden representations extracted from the single-channel TS-VAD model. Moreover, post-processing strategies for the predicted speaker activity probabilities are investigated. Experiments on the CHiME-6 unsegmented data show that TS-VAD achieves state-of-the-art results outperforming the baseline x-vector-based system by more than 30% Diarization Error Rate (DER) abs.Comment: Accepted to Interspeech 202

Correlation of LEND and Diviner Data

Correlated results from the Lunar Reconnaissance Orbiter's (LRO) Lunar Exploration Neutron Detector (LEND) and Lunar Orbiting Laser Altimeter (LOLA) suggest insolation effects influence the spatial distribution of Lunar H poleward of 60deg latitude. Diviner results indicate an insolation induced thermal contrast between pole-facing and equator-facing slopes of crater walls. Our research shows that the contrasting thermal conditions observed in pole-facing vs equator-facing slopes and epithermal neutron rates from LEND are positively correlated. Numerical transformations of LOLA topography facilitated a systematic decomposition of LEND epithermal maps as a function of insolation effects. The results suggest a significantly positive local epithermal contrast in these regions. Comparing pole-facing and equator-facing slopes, we find that the pole-facing slopes show epithermal neutron suppression ranging from -0.005 to 0.02 cps relative to the equator-facing slopes .. We further investigate insolation effects on epithermal neutrons by comparing the predicted insolation contrast derived from the 3-D LOLA topography model with the LEND results. We also investigate and discuss the possibility of slope mass wasting effects being correlated with our insolation-effect hypothesi

A First Search for coincident Gravitational Waves and High Energy Neutrinos using LIGO, Virgo and ANTARES data from 2007

We present the results of the first search for gravitational wave bursts associated with high energy neutrinos. Together, these messengers could reveal new, hidden sources that are not observed by conventional photon astronomy, particularly at high energy. Our search uses neutrinos detected by the underwater neutrino telescope ANTARES in its 5 line configuration during the period January - September 2007, which coincided with the fifth and first science runs of LIGO and Virgo, respectively. The LIGO-Virgo data were analysed for candidate gravitational-wave signals coincident in time and direction with the neutrino events. No significant coincident events were observed. We place limits on the density of joint high energy neutrino - gravitational wave emission events in the local universe, and compare them with densities of merger and core-collapse events.Comment: 19 pages, 8 figures, science summary page at http://www.ligo.org/science/Publication-S5LV_ANTARES/index.php. Public access area to figures, tables at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=p120000

Rationale for BepiColombo Studies of Mercury's Surface and Composition

BepiColombo has a larger and in many ways more capable suite of instruments relevant for determination of the topographic, physical, chemical and mineralogical properties of Mercury's surface than the suite carried by NASA's MESSENGER spacecraft. Moreover, BepiColombo's data rate is substantially higher. This equips it to confirm, elaborate upon, and go beyond many of MESSENGER's remarkable achievements. Furthermore, the geometry of BepiColombo's orbital science campaign, beginning in 2026, will enable it to make uniformly resolved observations of both northern and southern hemispheres. This will offer more detailed and complete imaging and topographic mapping, element mapping with better sensitivity and improved spatial resolution, and totally new mineralogical mapping. We discuss MESSENGER data in the context of preparing for BepiColombo, and describe the contributions that we expect BepiColombo to make towards increased knowledge and understanding of Mercury's surface and its composition. Much current work, including analysis of analogue materials, is directed towards better preparing ourselves to understand what BepiColombo might reveal. Some of MESSENGER's more remarkable observations were obtained under unique or extreme conditions. BepiColombo should be able to confirm the validity of these observations and reveal the extent to which they are representative of the planet as a whole. It will also make new observations to clarify geological processes governing and reflecting crustal origin and evolution. We anticipate that the insights gained into Mercury's geological history and its current space weathering environment will enable us to better understand the relationships of surface chemistry, morphologies and structures with the composition of crustal types, including the nature and mobility of volatile species. This will enable estimation of the composition of the mantle from which the crust was derived, and lead to tighter constraints on models for Mercury's origin including the nature and original heliocentric distance of the material from which it formed.Peer reviewe

Genetics of psycho-emotional well-being: genome-wide association study and polygenic risk score analysis

BackgroundPsycho-emotional well-being is essential for living a life of satisfaction and fulfillment. However, depression and anxiety have become the leading mental health issues worldwide, according to the World Health Organization. Both disorders have been linked to stress and other psychological factors. Their genetic basis remains understudied.MethodsIn 2020–2021, the psycho-emotional well-being of 30,063 Russians with no known psychiatric history was assessed using the Hospital Anxiety and Depression Scale (HADS) for general mental health and the HADS subscale A (anxiety) for anxiety. Following the original instructions, an anxiety score of ≥11 points was used as the anxiety threshold. A genome-wide association study was performed to find associations between anxiety and HADS/HADS-A scores using linear and logistic regressions based on HADS/HADS-A scores as binary and continuous variables, respectively. In addition, the links between anxiety, sociodemographic factors (such as age, sex, and employment), lifestyle (such as physical activity, sleep duration, and smoking), and markers of caffeine and alcohol metabolism were analyzed. To assess the risk of anxiety, polygenic risk score modeling was carried out using open-access software and principal component analysis (PCA) to simplify the calculations (ROC AUC = 89.4 ± 2.2% on the test set).ResultsThere was a strong positive association between HADS/HADS-A scores and sociodemographic factors and lifestyle. New single-nucleotide polymorphisms (SNPs) with genome-wide significance were discovered, which had not been associated with anxiety or other stress-related conditions but were located in genes previously associated with bipolar disorder, schizophrenia, or emotional instability. The CACNA1C variant rs1205787230 was associated with clinical anxiety (a HADS-A score of ≥11 points). There was an association between anxiety levels (HADS-A scores) and genes involved in the activity of excitatory neurotransmitters: PTPRN2 (rs3857647), DLGAP4 (rs8114927), and STK24 (rs9517326).ConclusionOur results suggest that calcium channels and monoamine neurotransmitters, as well as SNPs in genes directly or indirectly affecting neurogenesis and synaptic functions, may be involved in the development of increased anxiety. The role of some non-genetic factors and the clinical significance of physiological markers such as lifestyle were also demonstrated

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta