Speaker identification and clustering using convolutional neural networks

Deep learning, especially in the form of convolutional neural networks (CNNs), has triggered substantial improvements in computer vision and related fields in recent years. This progress is attributed to the shift from designing features and subsequent individual sub-systems towards learning features and recognition systems end to end from nearly unprocessed data. For speaker clustering, however, it is still common to use handcrafted processing chains such as MFCC features and GMM-based models. In this paper, we use simple spectrograms as input to a CNN and study the optimal design of those networks for speaker identification and clustering. Furthermore, we elaborate on the question how to transfer a network, trained for speaker identification, to speaker clustering. We demonstrate our approach on the well known TIMIT dataset, achieving results comparable with the state of the art – without the need for handcrafted features

Learning embeddings for speaker clustering based on voice equality

Recent work has shown that convolutional neural networks (CNNs) trained in a supervised fashion for speaker identification are able to extract features from spectrograms which can be used for speaker clustering. These features are represented by the activations of a certain hidden layer and are called embeddings. However, previous approaches require plenty of additional speaker data to learn the embedding, and although the clustering results are then on par with more traditional approaches using MFCC features etc., room for improvements stems from the fact that these embeddings are trained with a surrogate task that is rather far away from segregating unknown voices - namely, identifying few specific speakers. We address both problems by training a CNN to extract embeddings that are similar for equal speakers (regardless of their specific identity) using weakly labeled data. We demonstrate our approach on the well-known TIMIT dataset that has often been used for speaker clustering experiments in the past. We exceed the clustering performance of all previous approaches, but require just 100 instead of 590 unrelated speakers to learn an embedding suited for clustering

Indirect chiral magnetic exchange through Dzyaloshinskii–Moriya-enhanced RKKY interactions in manganese oxide chains on Ir(100)

Localized electron spins can couple magnetically via the Ruderman–Kittel–Kasuya–Yosida interaction even if their wave functions lack direct overlap. Theory predicts that spin–orbit scattering leads to a Dzyaloshinskii–Moriya type enhancement of this indirect exchange interaction, giving rise to chiral exchange terms. Here we present a combined spin-polarized scanning tunneling microscopy, angle-resolved photoemission, and density functional theory study of MnO_2 chains on Ir(100). Whereas we find antiferromagnetic Mn–Mn coupling along the chain, the inter-chain coupling across the non-magnetic Ir substrate turns out to be chiral with a 120° rotation between adjacent MnO_2 chains. Calculations reveal that the Dzyaloshinskii–Moriya interaction results in spin spirals with a periodicity in agreement with experiment. Our findings confirm the existence of indirect chiral magnetic exchange, potentially giving rise to exotic phenomena, such as chiral spin-liquid states in spin ice systems or the emergence of new quasiparticles

The fate of the 2√3 × 2√3R(30°) silicene phase on Ag(111)

Silicon atoms deposited on Ag(111) produce various single layer silicene sheets with different buckling patterns and periodicities. Low temperature scanning tunneling microscopy reveals that one of the silicene sheets, the hypothetical √7 × √7 silicene structure, on 2√3 × 2√3 Ag(111), is inherently highly defective and displays no long-range order. Moreover, Auger and photoelectron spectroscopy measurements reveal its sudden death, to end, in a dynamic fating process at ∼300 °C. This result clarifies the real nature of the 2√3 × 2√3R(30°) silicene phase and thus helps to understand the diversity of the silicene sheets grown on Ag(111)

Epitope-Specific Anti-C1q Autoantibodies in Systemic Lupus Erythematosus

OBJECTIVE: In patients with systemic lupus erythematosus (SLE) complement C1q is frequently targeted by autoantibodies (anti-C1q), that correlate best with active renal disease. Anti-C1q bind to largely unknown epitopes on the collagen-like region (CLR) of this highly functional molecule. Here we aimed at exploring the role of epitope-specific anti-C1q in SLE patients. METHODS: First, 22 sera of SLE patients, healthy controls and anti-C1q positive patients without SLE were screened for anti-C1q epitopes by a PEPperMAP(®) microarray, expressing CLR of C1q derived peptides with one amino acid (AA) shift in different lengths and conformations. Afterwards, samples of 378 SLE patients and 100 healthy blood donors were analyzed for antibodies against the identified epitopes by peptide-based ELISA. Relationships between peptide-specific autoantibodies and SLE disease manifestations were explored by logistic regression models. RESULTS: The epitope mapping showed increased IgG binding to three peptides of the C1q A- and three of the C1q B-chain. In subsequent peptide-based ELISAs, SLE sera showed significantly higher binding to two N-terminally located C1q A-chain peptides than controls (p < 0.0001), but not to the other peptides. While anti-C1q were associated with a broad spectrum of disease manifestations, some of the peptide-antibodies were associated with selected disease manifestations, and antibodies against the N-terminal C1q A-chain showed a stronger discrimination between SLE and controls than conventional anti-C1q. CONCLUSION: In this large explorative study anti-C1q correlate with SLE overall disease activity. In contrast, peptide-antibodies are associated with specific aspects of the disease suggesting epitope-specific effects of anti-C1q in patients with SLE

Many-body approach to proton emission and the role of spectroscopic factors

The process of proton emission from nuclei is studied by utilizing the two-potential approach of Gurvitz and Kalbermann in the context of the full many-body problem. A time-dependent approach is used for calculating the decay width. Starting from an initial many-body quasi-stationary state, we employ the Feshbach projection operator approach and reduce the formalism to an effective one-body problem. We show that the decay width can be expressed in terms of a one-body matrix element multiplied by a normalization factor. We demonstrate that the traditional interpretation of this normalization as the square root of a spectroscopic factor is only valid for one particular choice of projection operator. This causes no problem for the calculation of the decay width in a consistent microscopic approach, but it leads to ambiguities in the interpretation of experimental results. In particular, spectroscopic factors extracted from a comparison of the measured decay width with a calculated single-particle width may be affected.Comment: 17 pages, Revte

Cryo-EM structure of ex vivo fibrils associated with extreme AA amyloidosis prevalence in a cat shelter

AA amyloidosis is a systemic disease characterized by deposition of misfolded serum amyloid A protein (SAA) into cross-β amyloid in multiple organs in humans and animals. AA amyloidosis occurs at high SAA serum levels during chronic inflammation. Prion-like transmission was reported as possible cause of extreme AA amyloidosis prevalence in captive animals, e.g. 70% in cheetah and 57–73% in domestic short hair (DSH) cats kept in zoos and shelters, respectively. Herein, we present the 3.3 Å cryo-EM structure of AA amyloid extracted post-mortem from the kidney of a DSH cat with renal failure, deceased in a shelter with extreme disease prevalence. The structure reveals a cross-β architecture assembled from two 76-residue long proto-filaments. Despite >70% sequence homology to mouse and human SAA, the cat SAA variant adopts a distinct amyloid fold. Inclusion of an eight-residue insert unique to feline SAA contributes to increased amyloid stability. The presented feline AA amyloid structure is fully compatible with the 99% identical amino acid sequence of amyloid fragments of captive cheetah

Cryo-EM structure of ex vivo fibrils associated with extreme AA amyloidosis prevalence in a cat shelter.

AA amyloidosis is a systemic disease characterized by deposition of misfolded serum amyloid A protein (SAA) into cross-β amyloid in multiple organs in humans and animals. AA amyloidosis occurs at high SAA serum levels during chronic inflammation. Prion-like transmission was reported as possible cause of extreme AA amyloidosis prevalence in captive animals, e.g. 70% in cheetah and 57-73% in domestic short hair (DSH) cats kept in zoos and shelters, respectively. Herein, we present the 3.3 Å cryo-EM structure of AA amyloid extracted post-mortem from the kidney of a DSH cat with renal failure, deceased in a shelter with extreme disease prevalence. The structure reveals a cross-β architecture assembled from two 76-residue long proto-filaments. Despite >70% sequence homology to mouse and human SAA, the cat SAA variant adopts a distinct amyloid fold. Inclusion of an eight-residue insert unique to feline SAA contributes to increased amyloid stability. The presented feline AA amyloid structure is fully compatible with the 99% identical amino acid sequence of amyloid fragments of captive cheetah

MicroRNA-135b promotes cancer progression by acting as a downstream effector of oncogenic pathways in colon cancer

MicroRNA deregulation is frequent in human colorectal cancers (CRCs), but little is known as to whether it represents a bystander event or actually drives tumor progression in vivo. We show that miR-135b overexpression is triggered in mice and humans by APC loss, PTEN/PI3K pathway deregulation, and SRC overexpression and promotes tumor transformation and progression. We show that miR-135b upregulation is common in sporadic and inflammatory bowel disease-associated human CRCs and correlates with tumor stage and poor clinical outcome. Inhibition of miR-135b in CRC mouse models reduces tumor growth by controlling genes involved in proliferation, invasion, and apoptosis. We identify miR-135b as a key downsteam effector of oncogenic pathways and a potential target for CRC treatment

Indirect chiral magnetic exchange through Dzyaloshinskii–Moriya-enhanced RKKY interactions in manganese oxide chains on Ir(100)

Localized electron spins can couple magnetically via the Ruderman–Kittel–Kasuya–Yosida interaction even if their wave functions lack direct overlap. Theory predicts that spin–orbit scattering leads to a Dzyaloshinskii–Moriya type enhancement of this indirect exchange interaction, giving rise to chiral exchange terms. Here we present a combined spin-polarized scanning tunneling microscopy, angle-resolved photoemission, and density functional theory study of MnO_2 chains on Ir(100). Whereas we find antiferromagnetic Mn–Mn coupling along the chain, the inter-chain coupling across the non-magnetic Ir substrate turns out to be chiral with a 120° rotation between adjacent MnO_2 chains. Calculations reveal that the Dzyaloshinskii–Moriya interaction results in spin spirals with a periodicity in agreement with experiment. Our findings confirm the existence of indirect chiral magnetic exchange, potentially giving rise to exotic phenomena, such as chiral spin-liquid states in spin ice systems or the emergence of new quasiparticles