Detecting Dysfluencies in Stuttering Therapy Using wav2vec 2.0

Stuttering is a varied speech disorder that harms an individual's communication ability. Persons who stutter (PWS) often use speech therapy to cope with their condition. Improving speech recognition systems for people with such non-typical speech or tracking the effectiveness of speech therapy would require systems that can detect dysfluencies while at the same time being able to detect speech techniques acquired in therapy. This paper shows that fine-tuning wav2vec 2.0 [1] for the classification of stuttering on a sizeable English corpus containing stuttered speech, in conjunction with multi-task learning, boosts the effectiveness of the general-purpose wav2vec 2.0 features for detecting stuttering in speech; both within and across languages. We evaluate our method on FluencyBank , [2] and the German therapy-centric Kassel State of Fluency (KSoF) [3] dataset by training Support Vector Machine classifiers using features extracted from the finetuned models for six different stuttering-related event types: blocks, prolongations, sound repetitions, word repetitions, interjections, and - specific to therapy - speech modifications. Using embeddings from the fine-tuned models leads to relative classification performance gains up to 27% w.r.t. F1-score.Comment: Accepted at Interspeech 202

Electrostatic extraction of cold molecules from a cryogenic reservoir

We present a method which delivers a continuous, high-density beam of slow and internally cold polar molecules. In our source, warm molecules are first cooled by collisions with a cryogenic helium buffer gas. Cold molecules are then extracted by means of an electrostatic quadrupole guide. For ND$_3$ the source produces fluxes up to $(7 \pm ^{7}_{4}) \times 10^{10}$ molecules/s with peak densities up to $(1.0 \pm ^{1.0}_{0.6}) \times 10^9$ molecules/cm$^3$. For H$_2$CO the population of rovibrational states is monitored by depletion spectroscopy, resulting in single-state populations up to $(82 \pm 10)$.Comment: 4 pages, 4 figures, changes to the text, updated figures and reference

Fullerene-based Biocomponents : New Concepts For Functionalising Membranes

Lipophilic hexakisadducts of fullerene C60 form unprecedented rod-like nanoaggregates in phospholipid-membrane bilayers, resulting in modification of the micromechanic properties and stabilisation of the membrane. Lipofullerenes with amphiphilic side chains enable additionally derivatisation and molecular recognition at the membrane surface. The amphiphilic spacer acts as a transmembrane anchor and provides the terminal functionality outside of the membrane. New systems derived from parent compound 3 carry two functional groups each and can be easily modified due to the modular synthesis. Terminal functionalities to be investigated include D(+)-biotin and IDA (iminodiacetic acid) ligands, as used in nickel-histidine tags. Modification of the lipophilic region, for instance with unsaturated addends is also possible. These addends should allow polymerisation inside the membrane and potentially lead to a tremendous increase of the membrane rigidity. Furthermore, mono- and bilayer-forming fullerene derivatives without the membrane-forming support of lecithins are investigated and exhibit interesting features

Surveillance and falsification implications for open source intelligence investigations

© 2015 ACM. Legitimacy of surveillance is crucial to safeguarding validity of OSINT data as a tool for law-enforcement agencies

A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem

Most stuttering detection and classification research has viewed stuttering as a multi-class classification problem or a binary detection task for each dysfluency type; however, this does not match the nature of stuttering, in which one dysfluency seldom comes alone but rather co-occurs with others. This paper explores multi-language and cross-corpus end-to-end stuttering detection as a multi-label problem using a modified wav2vec 2.0 system with an attention-based classification head and multi-task learning. We evaluate the method using combinations of three datasets containing English and German stuttered speech, one containing speech modified by fluency shaping. The experimental results and an error analysis show that multi-label stuttering detection systems trained on cross-corpus and multi-language data achieve competitive results but performance on samples with multiple labels stays below over-all detection results.Comment: Accepted for presentation at Interspeech 2023. arXiv admin note: substantial text overlap with arXiv:2210.1598

Multi-class Detection of Pathological Speech with Latent Features: How does it perform on unseen data?

The detection of pathologies from speech features is usually defined as a binary classification task with one class representing a specific pathology and the other class representing healthy speech. In this work, we train neural networks, large margin classifiers, and tree boosting machines to distinguish between four different pathologies: Parkinson's disease, laryngeal cancer, cleft lip and palate, and oral squamous cell carcinoma. We demonstrate that latent representations extracted at different layers of a pre-trained wav2vec 2.0 system can be effectively used to classify these types of pathological voices. We evaluate the robustness of our classifiers by adding room impulse responses to the test data and by applying them to unseen speech corpora. Our approach achieves unweighted average F1-Scores between 74.1% and 96.4%, depending on the model and the noise conditions used. The systems generalize and perform well on unseen data of healthy speakers sampled from a variety of different sources.Comment: Submitted to ICASSP 202

Storage and Adiabatic Cooling of Polar Molecules in a Microstructured Trap

We present a versatile electric trap for the exploration of a wide range of quantum phenomena in the interaction between polar molecules. The trap combines tunable fields, homogeneous over most of the trap volume, with steep gradient fields at the trap boundary. An initial sample of up to 10^8 CH3F molecules is trapped for as long as 60 seconds, with a 1/e storage time of 12 seconds. Adiabatic cooling down to 120 mK is achieved by slowly expanding the trap volume. The trap combines all ingredients for opto-electrical cooling, which, together with the extraordinarily long storage times, brings field-controlled quantum-mechanical collision and reaction experiments within reach

Classifying Dementia in the Presence of Depression: A Cross-Corpus Study

Automated dementia screening enables early detection and intervention, reducing costs to healthcare systems and increasing quality of life for those affected. Depression has shared symptoms with dementia, adding complexity to diagnoses. The research focus so far has been on binary classification of dementia (DEM) and healthy controls (HC) using speech from picture description tests from a single dataset. In this work, we apply established baseline systems to discriminate cognitive impairment in speech from the semantic Verbal Fluency Test and the Boston Naming Test using text, audio and emotion embeddings in a 3-class classification problem (HC vs. MCI vs. DEM). We perform cross-corpus and mixed-corpus experiments on two independently recorded German datasets to investigate generalization to larger populations and different recording conditions. In a detailed error analysis, we look at depression as a secondary diagnosis to understand what our classifiers actually learn.Comment: Accepted at INTERSPEECH 202

Intense Atomic and Molecular Beams via Neon Buffer Gas Cooling

We realize a continuous guided beam of cold deuterated ammonia with a flux of 3e11 ND3 molecules/s and a continuous free-space beam of cold potassium with a flux of 1e16 K atoms/s. A novel feature of the buffer gas source used to produce these beams is cold neon, which, due to intermediate Knudsen number beam dynamics, produces a forward velocity and low-energy tail that is comparable to much colder helium-based sources. We expect this source to be trivially generalizable to a very wide range of atomic and molecular species with significant vapor pressure below 1000 K. This source has properties that make it a good starting point for laser cooling of molecules or atoms, cold collision studies, trapping, or nonlinear optics in buffer-gas-cooled atomic or molecular gases.Comment: 15 pages, 6 figure